From eec96dfcf6fddadb6e11dcd6664efad52ea2acdf Mon Sep 17 00:00:00 2001 From: Maziyar Panahi Date: Mon, 11 Sep 2023 12:59:44 +0200 Subject: [PATCH] Models hub (#13972) --------- Co-authored-by: ahmedlone127 * 2023-08-28-asr_whisper_tiny_opt_xx (#13944) * Add model 2023-08-28-asr_whisper_tiny_opt_xx * Update 2023-08-28-asr_whisper_tiny_opt_xx.md Change Spark Version * Update 2023-08-28-asr_whisper_tiny_opt_xx.md Spark version 3.0 * Update 2023-08-28-asr_whisper_tiny_opt_xx.md spark version * Update 2023-08-28-asr_whisper_tiny_opt_xx.md --------- Co-authored-by: DevinTDHa Co-authored-by: Devin Ha <33089471+DevinTDHa@users.noreply.github.com> * 2023-09-07-java_pointer_classifier_en (#13968) * Add model 2023-09-07-invoiceornot_en * Add model 2023-09-07-biolord_stamb2_v1_en * Add model 2023-09-07-cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en * Add model 2023-09-07-tiny_random_mpnetmodel_hf_internal_testing_en * Add model 2023-09-07-ikitracs_mitigation_en * Add model 2023-09-07-mpnet_snli_en * Add model 2023-09-07-sml_ukr_message_classifier_en * Add model 2023-09-07-action_policy_plans_classifier_en * Add model 2023-09-07-nooks_amd_detection_v2_full_en * Add model 2023-09-07-tiny_random_mpnetformultiplechoice_en * Add model 2023-09-07-all_datasets_v4_mpnet_base_en * Add model 2023-09-07-review_intent_20230116_en * Add model 2023-09-07-tiny_random_mpnetfortokenclassification_hf_tiny_model_private_en * Add model 2023-09-07-multi_qa_v1_mpnet_asymmetric_q_en * Add model 2023-09-07-tiny_random_mpnetmodel_hf_tiny_model_private_en * Add model 2023-09-07-setfit_alpaca_spanish_unprocessable_sample_detection_es * Add model 2023-09-07-nps_psb_lds_en * Add model 2023-09-07-github_issues_mpnet_southern_sotho_e10_en * Add model 2023-09-07-mpnet_retriever_squad2_en * Add model 2023-09-07-mpnet_adaptation_mitigation_classifier_en * Add model 2023-09-07-stackoverflow_mpnet_base_en * Add model 2023-09-07-all_mpnet_base_v2_diptanuc_en * Add model 2023-09-07-setfit_model_pradipta11_en * Add model 2023-09-07-setfit_zero_shot_classification_pbsp_p1_life_en * Add model 2023-09-07-due_retail_25_en * Add model 2023-09-07-java_summary_classifier_en * Add model 2023-09-07-tiny_random_mpnetforsequenceclassification_hf_tiny_model_private_en * Add model 2023-09-07-multi_qa_v1_mpnet_asymmetric_a_en * Add model 2023-09-07-all_mpnet_base_v2_sentence_transformers_en * Add model 2023-09-07-setfit_ds_version_0_0_2_en * Add model 2023-09-07-multi_qa_mpnet_base_cos_v1_sentence_transformers_en * Add model 2023-09-07-setfit_ds_version_0_0_4_en * Add model 2023-09-07-java_expand_classifier_en * Add model 2023-09-07-python_summary_classifier_en * Add model 2023-09-07-test_food_en * Add model 2023-09-07-sbert_paper_en * Add model 2023-09-07-setfit_model_rajistics_en * Add model 2023-09-07-all_mpnet_base_v2_embedding_all_en * Add model 2023-09-07-due_eshop_21_multilabel_en * Add model 2023-09-07-initial_model_v3_en * Add model 2023-09-07-retriever_coding_guru_adapted_en * Add model 2023-09-07-paraphrase_mpnet_base_v2_fuzzy_matcher_en * Add model 2023-09-07-setfit_ethos_multilabel_example_lewtun_en * Add model 2023-09-07-python_expand_classifier_en * Add model 2023-09-07-kw_classification_setfit_model_en * Add model 2023-09-07-pharo_collaborators_classifier_en * Add model 2023-09-07-mpnet_base_articles_ner_en * Add model 2023-09-07-shona_mpnet_base_snli_mnli_en * Add model 2023-09-07-fail_detect_en * Add model 2023-09-07-python_usage_classifier_en * Add model 2023-09-07-invoiceornot_en * Add model 2023-09-07-tiny_random_mpnetforquestionanswering_hf_internal_testing_en * Add model 2023-09-07-cpu_netzero_classifier_en * Add model 2023-09-07-pharo_responsibilities_classifier_en * Add model 2023-09-07-all_mpnet_base_v2_obrizum_en * Add model 2023-09-07-tiny_random_mpnetmodel_hf_internal_testing_en * Add model 2023-09-07-tiny_random_mpnetfortokenclassification_hf_internal_testing_en * Add model 2023-09-07-tiny_random_mpnet_hf_internal_testing_en * Add model 2023-09-07-python_developmentnotes_classifier_en * Add model 2023-09-08-test_model_001_en * Add model 2023-09-07-covid_qa_mpnet_en * Add model 2023-09-08-setfit_ostrom_en * Add model 2023-09-08-patentsberta_v2_en * Add model 2023-09-07-pdfsegs_en * Add model 2023-09-07-mpnet_snli_negatives_en * Add model 2023-09-08-eth_setfit_payment_model_en * Add model 2023-09-08-all_mpnet_base_questions_clustering_english_en * Add model 2023-09-08-esci_jp_mpnet_crossencoder_en * Add model 2023-09-07-kw_classification_setfithead_model_en * Add model 2023-09-08-setfit_zero_shot_classification_pbsp_p4_time_en * Add model 2023-09-07-579_stmodel_product_rem_v3a_en * Add model 2023-09-07-tiny_random_mpnetformaskedlm_hf_internal_testing_en * Add model 2023-09-07-setfit_all_data_en * Add model 2023-09-07-review_multiclass_20230116_en * Add model 2023-09-07-nli_mpnet_base_v2_sentence_transformers_en * Add model 2023-09-07-reddit_single_context_mpnet_base_en * Add model 2023-09-07-tiny_random_mpnetforsequenceclassification_hf_internal_testing_en * Add model 2023-09-07-java_rational_classifier_en * Add model 2023-09-08-setfit_zero_shot_classification_pbsp_p3_bhvr_en * Add model 2023-09-07-all_mpnet_base_v2_tasky_classification_en * Add model 2023-09-08-setfit_zero_shot_classification_pbsp_p4_meas_en * Add model 2023-09-07-sb_temfac_en * Add model 2023-09-07-sb_temfac_en * Add model 2023-09-07-all_mpnet_base_v2_ftlegal_v3_en * Add model 2023-09-07-pharo_collaborators_classifier_en * Add model 2023-09-08-all_mpnet_base_v2_feature_extraction_en * Add model 2023-09-08-setfit_zero_shot_classification_pbsp_p4_achiev_en * Add model 2023-09-07-cpu_economywide_classifier_en * Add model 2023-09-08-setfit_zero_shot_classification_pbsp_p4_rel_en * Add model 2023-09-07-all_mpnet_base_v2_sentence_transformers_en * Add model 2023-09-08-setfit_zero_shot_classification_pbsp_p3_cons_en * Add model 2023-09-07-setfit_ds_version_0_0_5_en * Add model 2023-09-07-cpu_conditional_classifier_en * Add model 2023-09-07-all_mpnet_base_v2_table_en * Add model 2023-09-07-ikitracs_mitigation_en * Add model 2023-09-07-vulnerable_groups_en * Add model 2023-09-08-setfit_zero_shot_classification_pbsp_p4_specific_en * Add model 2023-09-07-tiny_random_mpnetforsequenceclassification_hf_tiny_model_private_en * Add model 2023-09-07-tiny_random_mpnetforquestionanswering_hf_tiny_model_private_en * Add model 2023-09-07-multi_qa_v1_mpnet_asymmetric_a_en * Add model 2023-09-07-biencoder_all_mpnet_base_v2_mmarcofr_fr * Add model 2023-09-07-initial_model_en * Add model 2023-09-07-sentiment140_fewshot_en * Add model 2023-09-07-python_summary_classifier_en * Add model 2023-09-08-cpu_target_classifier_en * Add model 2023-09-07-ikitracs_conditional_en * Add model 2023-09-07-setfit_ag_news_endpoint_en * Add model 2023-09-08-setfit_model_feb11_misinformation_on_law_en * Add model 2023-09-07-multi_qa_mpnet_base_dot_v1_sentence_transformers_en * Add model 2023-09-08-setfit_zero_shot_classification_pbsp_q8a_azure_gpt35_en * Add model 2023-09-07-mpnet_multilabel_sector_classifier_en * Add model 2023-09-08-paraphrase_mpnet_base_v2_finetuned_polifact_en * Add model 2023-09-07-all_datasets_v3_mpnet_base_en * Add model 2023-09-08-all_mpnet_base_v2_for_sb_clustering_en * Add model 2023-09-07-negation_categories_classifier_es * Add model 2023-09-07-python_parameters_classifier_en * Add model 2023-09-07-due_eshop_21_en * Add model 2023-09-07-contradiction_psb_en * Add model 2023-09-07-mpnet_mnr_v2_fine_tuned_en * Add model 2023-09-07-labels_per_job_title_fine_tune_en * Add model 2023-09-07-paraphrase_mpnet_base_v2_sentence_transformers_en * Add model 2023-09-07-all_datasets_v4_mpnet_base_en * Add model 2023-09-07-pharo_example_classifier_en * Add model 2023-09-07-paraphrase_mpnet_base_v2_setfit_sst2_en * Add model 2023-09-07-all_mpnet_base_v2_ftlegal_v3_en * Add model 2023-09-07-mpnet_adaptation_mitigation_classifier_en * Add model 2023-09-07-abstract_sim_query_en * Add model 2023-09-07-python_developmentnotes_classifier_en * Add model 2023-09-08-few_shot_model_en * Add model 2023-09-07-tiny_random_mpnetformaskedlm_hf_tiny_model_private_en * Add model 2023-09-07-biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr_fr * Add model 2023-09-07-cpu_economywide_classifier_en * Add model 2023-09-07-contradiction_psb_lds_en * Add model 2023-09-07-setfit_ds_version_0_0_1_en * Add model 2023-09-07-kw_classification_setfit_model_en * Add model 2023-09-07-all_mpnet_base_v2_finetuned_v2_en * Add model 2023-09-07-mpnet_base_snli_mnli_en * Add model 2023-09-07-tiny_random_mpnetformaskedlm_hf_internal_testing_en * Add model 2023-09-07-mpnet_base_snli_mnli_en * Add model 2023-09-07-multi_qa_v1_mpnet_cls_dot_en * Add model 2023-09-07-tiny_random_mpnetforquestionanswering_hf_tiny_model_private_en * Add model 2023-09-07-setfit_zero_shot_classification_pbsp_p1_likes_en * Add model 2023-09-07-nooks_amd_detection_realtime_en * Add model 2023-09-07-setfit_zero_shot_classification_pbsp_p1_en * Add model 2023-09-07-github_issues_mpnet_southern_sotho_e10_en * Add model 2023-09-07-burmese_awesome_setfit_model_98_en * Add model 2023-09-07-setfit_few_shot_classifier_en * Add model 2023-09-07-pdfsegs_en * Add model 2023-09-07-mpnet_snli_en * Add model 2023-09-07-abstract_sim_query_en * Add model 2023-09-07-pharo_keyimplementationpoints_classifier_en * Add model 2023-09-07-abstract_sim_sentence_en * Add model 2023-09-07-all_mpnet_base_v2_feature_extraction_pipeline_en * Add model 2023-09-07-shona_mpnet_base_snli_mnli_en * Add model 2023-09-07-nooks_amd_detection_realtime_en * Add model 2023-09-07-pharo_keyimplementationpoints_classifier_en * Add model 2023-09-07-domainadaptm2_en * Add model 2023-09-07-setfit_finetuned_financial_text_en * Add model 2023-09-07-cpu_mitigation_classifier_en * Add model 2023-09-07-sml_ukr_word_classifier_medium_en * Add model 2023-09-07-java_expand_classifier_en * Add model 2023-09-07-tiny_random_mpnetforsequenceclassification_hf_internal_testing_en * Add model 2023-09-07-setfit_zero_shot_classification_pbsp_p1_comm_en * Add model 2023-09-07-setfit_ds_version_0_0_2_en * Add model 2023-09-07-setfit_zero_shot_classification_pbsp_p3_func_en * Add model 2023-09-07-mpnet_multilabel_sector_classifier_en * Add model 2023-09-07-all_mpnet_base_v2_finetuned_v2_en * Add model 2023-09-07-ouvrage_classif_en * Add model 2023-09-07-setfit_zero_shot_classification_pbsp_p3_sev_en * Add model 2023-09-07-kw_classification_setfithead_model_en * Add model 2023-09-07-setfit_zero_shot_classification_pbsp_p1_en * Add model 2023-09-07-tiny_random_mpnetformultiplechoice_en * Add model 2023-09-07-setfit_model_test_sensitve_v1_en * Add model 2023-09-07-spiced_en * Add model 2023-09-07-mpnet_nli_sts_en * Add model 2023-09-07-java_deprecation_classifier_en * Add model 2023-09-07-cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en * Add model 2023-09-07-test_food_en * Add model 2023-09-07-testing_setfit_en * Add model 2023-09-07-multi_qa_mpnet_base_dot_v1_eclass_en * Add model 2023-09-07-ecolo_pas_ecolo_v0.1_en * Add model 2023-09-07-mpnet_retriever_squad2_en * Add model 2023-09-07-github_issues_preprocessed_mpnet_southern_sotho_e10_en * Add model 2023-09-07-stsb_mpnet_base_v2_en * Add model 2023-09-07-sentence_transformers_bible_reference_final_en * Add model 2023-09-07-setfit_all_data_en * Add model 2023-09-07-ouvrage_classif_en * Add model 2023-09-07-all_mpnet_base_v1_en * Add model 2023-09-07-all_mpnet_base_v1_en * Add model 2023-09-07-ouvrage_classif_en * Add model 2023-09-07-mpnet_nli_sts_en * Add model 2023-09-07-tiny_random_mpnetforquestionanswering_hf_tiny_model_private_en * Add model 2023-09-07-sml_ukr_word_classifier_medium_en * Add model 2023-09-07-vulnerable_groups_en * Add model 2023-09-07-python_expand_classifier_en * Add model 2023-09-07-all_mpnet_base_v2_tasky_classification_en * Add model 2023-09-07-biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr_fr * Add model 2023-09-07-java_ownership_classifier_en * Add model 2023-09-07-multi_qa_mpnet_base_cos_v1_navteca_en * Add model 2023-09-07-setfit_zero_shot_classification_pbsp_p3_sev_en * Add model 2023-09-07-biolord_stamb2_v1_en * Add model 2023-09-07-java_pointer_classifier_en * Add model 2023-09-07-reddit_single_context_mpnet_base_en * Add model 2023-09-07-setfit_finetuned_financial_text_en * Add model 2023-09-07-cpu_transport_ghg_classifier_en * Add model 2023-09-08-setfit_zero_shot_classification_pbsp_p3_trig_en * Add model 2023-09-07-paraphrase_mpnet_base_v2_sentence_transformers_en * Add model 2023-09-07-579_stmodel_product_rem_v3a_en * Add model 2023-09-07-multi_qa_mpnet_base_dot_v1_eclass_en * Add model 2023-09-07-nps_psb_lds_en * Add model 2023-09-07-negation_categories_classifier_es * Add model 2023-09-08-setfit_zero_shot_classification_pbsp_p3_dur_en * Add model 2023-09-07-mpnet_mnr_v2_fine_tuned_en * Add model 2023-09-07-keyphrase_mpnet_v1_en * Add model 2023-09-07-cpu_mitigation_classifier_en * Add model 2023-09-07-multi_qa_mpnet_base_cos_v1_navteca_en * Add model 2023-09-07-setfit_model_test_sensitve_v1_en * Add model 2023-09-07-spiced_en * Add model 2023-09-07-ecolo_pas_ecolo_v0.1_en * Add model 2023-09-07-paraphrase_mpnet_base_v2_setfit_sst2_en * Add model 2023-09-07-setfit_ds_version_0_0_1_en * Add model 2023-09-08-multi_qa_mpnet_base_dot_v1_model_embeddings_en * Add model 2023-09-07-setfit_occupation_en * Add model 2023-09-07-multi_qa_mpnet_base_dot_v1_legal_finetune_en * Add model 2023-09-07-burmese_awesome_setfit_model_en * Add model 2023-09-07-multi_qa_v1_mpnet_cls_dot_en * Add model 2023-09-07-tiny_random_mpnetfortokenclassification_hf_internal_testing_en * Add model 2023-09-07-setfit_ethos_multilabel_example_neilthematic_en * Add model 2023-09-07-keyphrase_mpnet_v1_en * Add model 2023-09-07-fewshotissueclassifier_nlbse23_en * Add model 2023-09-07-stsb_mpnet_base_v2_en * Add model 2023-09-07-all_mpnet_base_v2_obrizum_en * Add model 2023-09-08-setfit_ft_sentinent_eval_en * Add model 2023-09-07-attack_bert_en * Add model 2023-09-07-all_datasets_v3_mpnet_base_en * Add model 2023-09-07-cpu_transport_ghg_classifier_en * Add model 2023-09-07-fewshotissueclassifier_nlbse23_en * Add model 2023-09-07-java_deprecation_classifier_en * Add model 2023-09-07-java_usage_classifier_en * Add model 2023-09-07-sbert_paper_en * Add model 2023-09-07-setfit_ethos_multilabel_example_neilthematic_en * Add model 2023-09-07-patentsberta_en * Add model 2023-09-07-setfit_occupation_en * Add model 2023-09-07-setfit_ds_version_0_0_5_en * Add model 2023-09-07-mpnet_snli_negatives_en * Add model 2023-09-08-nli_mpnet_base_v2_en * Add model 2023-09-08-multi_qa_mpnet_base_cos_v1_en * Add model 2023-09-08-multi_qa_mpnet_base_dot_v1_en * Add model 2023-09-08-all_mpnet_base_v2_en * Add model 2023-09-08-paraphrase_mpnet_base_v2_en --------- Co-authored-by: ahmedlone127 * 2023-09-09-medium_mlm_imdb_en (#13970) * Add model 2023-09-09-medium_mlm_imdb_en * Add model 2023-09-09-bert_base_cased_finetuned_mrpc_en * Add model 2023-09-09-base_mlm_imdb_en * Add model 2023-09-09-vbert_2021_large_en * Add model 2023-09-09-bert_base_german_dbmdz_cased_de * Add model 2023-09-09-arabic_mbertmodel_mberttok_en * Add model 2023-09-09-bert_base_german_dbmdz_uncased_de * Add model 2023-09-09-arabic_mbertmodel_monotok_adapter_en * Add model 2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8_en * Add model 2023-09-09-kw_pubmed_5000_0.0003_en * Add model 2023-09-09-bertunam_en * Add model 2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9_en * Add model 2023-09-09-arabic_mbertmodel_monotok_en * Add model 2023-09-09-kw_pubmed_10000_0.00006_en * Add model 2023-09-09-arabic_monomodel_mberttok_en * Add model 2023-09-09-bert_base_uncased_issues_128_susnato_en * Add model 2023-09-09-bert_large_uncased_whole_word_masking_en * Add model 2023-09-09-finnish_mbertmodel_mberttok_en * Add model 2023-09-09-kw_pubmed_10000_0.0003_en * Add model 2023-09-09-kw_pubmed_5000_0.000006_en * Add model 2023-09-09-bertimbau_large_fine_tuned_md_en * Add model 2023-09-09-lsg16k_italian_legal_bert_it * Add model 2023-09-09-finnish_mbertmodel_monotok_en * Add model 2023-09-09-alephbertgimmel_20_epochs_en * Add model 2023-09-09-kw_pubmed_5000_0.00006_en * Add model 2023-09-09-arabic_monomodel_monotok_en * Add model 2023-09-09-aethiqs_gembert_bertje_50k_en * Add model 2023-09-09-bert_nlp_project_news_en * Add model 2023-09-09-dummy_model2_en * Add model 2023-09-09-aethiqs_base_bertje_data_rotterdam_epochs_10_en * Add model 2023-09-09-bert_large_cased_whole_word_masking_en * Add model 2023-09-09-alephbertgimmel_10_epochs_en * Add model 2023-09-09-indonesian_mbertmodel_mberttok_en * Add model 2023-09-09-kw_pubmed_10000_0.000006_en * Add model 2023-09-09-indonesian_mbertmodel_monotok_en * Add model 2023-09-09-s3_v1_20_epochs_en * Add model 2023-09-09-bert_base_uncased_semeval2014_en * Add model 2023-09-09-indonesian_monomodel_mberttok_en * Add model 2023-09-09-bertimbau_large_fine_tuned_sindhi_en * Add model 2023-09-09-bert_srb_base_cased_oscar_en * Add model 2023-09-09-prompt_finetune_en * Add model 2023-09-09-bert_large_uncased_semeval2014_en * Add model 2023-09-09-finnish_monomodel_mberttok_en * Add model 2023-09-09-indonesian_mbertmodel_monotok_adapter_en * Add model 2023-09-09-bert_base_parsbert_uncased_finetuned_en * Add model 2023-09-09-korean_mbertmodel_mberttok_en * Add model 2023-09-09-finnish_monomodel_monotok_en * Add model 2023-09-09-finnish_mbertmodel_monotok_adapter_en * Add model 2023-09-09-indonesian_monomodel_monotok_en * Add model 2023-09-09-covid_trained_bert_en * Add model 2023-09-09-alephbertgimmel_50_epochs_en * Add model 2023-09-09-wordpred_arabert_en * Add model 2023-09-09-aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30_en * Add model 2023-09-09-newsbert_en * Add model 2023-09-09-biodivbert_en * Add model 2023-09-09-bert_base_arabic_camelbert_catalan_ar * Add model 2023-09-09-korean_monomodel_mberttok_en * Add model 2023-09-09-bert_random_weights_en * Add model 2023-09-09-bert_base_arabic_camelbert_danish_ar * Add model 2023-09-09-bert_gb_2021_en * Add model 2023-09-09-turkish_mbertmodel_mberttok_en * Add model 2023-09-09-bert_large_uncased_semeval2014_restaurants_en * Add model 2023-09-09-turkish_mbertmodel_monotok_adapter_en * Add model 2023-09-09-pt_pol_en * Add model 2023-09-09-bert_base_arabic_camelbert_msa_eighth_ar * Add model 2023-09-09-bert_base_arabic_camelbert_msa_half_ar * Add model 2023-09-09-turkish_mbertmodel_monotok_en * Add model 2023-09-09-bert_base_arabic_camelbert_msa_quarter_ar * Add model 2023-09-09-turkish_monomodel_mberttok_en * Add model 2023-09-09-bert_base_arabic_camelbert_mix_ar * Add model 2023-09-09-csci544_project_mabel_en * Add model 2023-09-09-turkish_monomodel_monotok_en * Add model 2023-09-09-gujbert_senti_a_en * Add model 2023-09-09-bert_base_arabic_camelbert_msa_ar * Add model 2023-09-09-javabert_uncased_en * Add model 2023-09-09-bert_base_arabic_camelbert_msa_sixteenth_ar * Add model 2023-09-09-pt_legalbert_en * Add model 2023-09-09-bert_large_uncased_semeval2014_laptops_en * Add model 2023-09-09-bert_large_uncased_semeval2015_restaurants_en * Add model 2023-09-09-bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies_en * Add model 2023-09-09-spacescibert_en * Add model 2023-09-09-bert_base_nli_ct_en * Add model 2023-09-09-bert_base_ct_en * Add model 2023-09-09-pt_caselawbert_en * Add model 2023-09-09-hubert_base_cc_finetuned_forum_en * Add model 2023-09-09-xtreme_squad_bert_base_multilingual_cased_xx * Add model 2023-09-09-bert_racism_en * Add model 2023-09-09-mymodel04_illvmi_en * Add model 2023-09-09-bert_racism15_en * Add model 2023-09-09-bert_large_nli_ct_en * Add model 2023-09-09-jobbert_test_org_trial_26_12_2022_en * Add model 2023-09-09-bert_large_uncased_semeval2016_restaurants_en * Add model 2023-09-09-bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies_en * Add model 2023-09-09-bert_large_uncased_semeval2015_laptops_en * Add model 2023-09-09-bert_base_irish_cased_v1_en * Add model 2023-09-09-bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies_en * Add model 2023-09-09-indobertweet_base_uncased_id * Add model 2023-09-09-bert_large_ct_en * Add model 2023-09-09-jobbert_org_add_words_trial_26_12_2022_en * Add model 2023-09-09-indobert_base_uncased_id * Add model 2023-09-09-bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies_en * Add model 2023-09-09-bert_base_uncased_dish_descriptions_128_en * Add model 2023-09-09-inlegalbert_cbp_lkg_triples_finetuned_en * Add model 2023-09-09-spacebert_en * Add model 2023-09-09-javabert_en * Add model 2023-09-09-bert_large_uncased_semeval2016_laptops_en * Add model 2023-09-09-bert_base_multilingual_cased_finetuned_hausa_xx * Add model 2023-09-09-bert_base_uncased_dish_descriptions_128_0.5m_en * Add model 2023-09-09-jobbert_org_add_words_trial_26_12_2022_en * Add model 2023-09-09-bert_base_multilingual_cased_finetuned_hausa_xx * Add model 2023-09-09-bert_base_uncased_fined_en * Add model 2023-09-09-bert_ucb_3_en * Add model 2023-09-09-bert_base_multilingual_cased_finetuned_igbo_xx * Add model 2023-09-09-jobbert_org_add_words_v2_trial_26_12_2022_en * Add model 2023-09-09-tod_bert_jnt_en * Add model 2023-09-09-scholarbert_en * Add model 2023-09-09-legal_bert_base_uncased_finetuned_ledgarscotus7_en * Add model 2023-09-09-bert_base_multilingual_cased_finetuned_kinyarwanda_xx * Add model 2023-09-09-bert_tagalog_base_cased_wwm_tl * Add model 2023-09-09-bert_base_uncased_zhibinhong_en * Add model 2023-09-09-bert_tagalog_base_cased_tl * Add model 2023-09-09-bert__racism80000_en * Add model 2023-09-09-bert_tagalog_base_uncased_wwm_tl * Add model 2023-09-09-scholarbert_10_en * Add model 2023-09-09-bert_base_multilingual_cased_finetuned_luganda_xx * Add model 2023-09-09-bert_large_uncased_facebook_election_ads_en * Add model 2023-09-09-kinyabert_small_en * Add model 2023-09-09-bert_base_multilingual_cased_finetuned_swahili_xx * Add model 2023-09-09-bert_base_multilingual_cased_finetuned_dholuo_xx * Add model 2023-09-09-bert_hateracism90000_en * Add model 2023-09-09-scholarbert_1_en * Add model 2023-09-09-mtl_bert_base_uncased_en * Add model 2023-09-09-bert_base_multilingual_cased_finetuned_wolof_xx * Add model 2023-09-09-bert_base_multilingual_cased_finetuned_yoruba_xx * Add model 2023-09-09-kinyabert_large_en * Add model 2023-09-09-medbert_breastcancer_en * Add model 2023-09-09-scholarbert_10_wb_en * Add model 2023-09-09-kbert_base_esg_e10_en * Add model 2023-09-09-alglegal3_bert_base_arabertv2_en * Add model 2023-09-09-kbert_base_esg_e3_en * Add model 2023-09-09-bert_large_portuguese_cased_legal_tsdae_pt * Add model 2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0_en * Add model 2023-09-09-kbert_base_esg_e5_en * Add model 2023-09-09-mtl_bert_base_uncased_ww_en * Add model 2023-09-09-mlm_20230427_indobertlarge_001_en * Add model 2023-09-09-kaz_legal_bert_en * Add model 2023-09-09-bert_ucb_4_en * Add model 2023-09-09-mlm_20230427_mbert_001_en * Add model 2023-09-09-scholarbert_100_wb_en * Add model 2023-09-09-bert_sparql_en * Add model 2023-09-09-kaz_legal_bert_5_en * Add model 2023-09-09-knowbias_bert_base_uncased_gender_en * Add model 2023-09-09-bert_tagalog_base_uncased_tl * Add model 2023-09-09-bert_base_arabertv2_algarlegalbert_en * Add model 2023-09-09-sae_bert_base_uncased_en * Add model 2023-09-09-bert_base_multilingual_cased_finetuned_naija_xx * Add model 2023-09-09-bantu_bert_xx * Add model 2023-09-09-adaptive_lm_molecules_en * Add model 2023-09-09-bert_base_portuguese_cased_test_server_en * Add model 2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2_en * Add model 2023-09-09-nepali_bert_npvec1_en * Add model 2023-09-09-jzmodel01_en * Add model 2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3_en * Add model 2023-09-09-biomednlp_pubmedbert_large_uncased_abstract_en * Add model 2023-09-09-bert_base_uncased_finetune_security_en * Add model 2023-09-09-guidebias_bert_base_uncased_gender_en * Add model 2023-09-09-arabert32_flickr8k_en * Add model 2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4_en * Add model 2023-09-09-metaphor_finetuned_bert_5epochs_en * Add model 2023-09-09-indojave_codemixed_indobertweet_base_id * Add model 2023-09-09-tiny_mlm_snli_en * Add model 2023-09-09-bert_base_uncased_issues_128_tanviraumi_en * Add model 2023-09-09-romanian_bert_tweet_ro * Add model 2023-09-09-tendencias_en * Add model 2023-09-09-bert_base_aeslc_danish_en * Add model 2023-09-09-materialsbert_en * Add model 2023-09-09-222_en * Add model 2023-09-09-bert_base_aeslc_aktsvigun_en * Add model 2023-09-09-dfm_encoder_large_v1_da * Add model 2023-09-09-ai12_junzai_en * Add model 2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5_en * Add model 2023-09-09-bert_large_portuguese_cased_legal_mlm_pt * Add model 2023-09-09-bert_finetuning_test1227_hug_en * Add model 2023-09-09-german_poetry_bert_en * Add model 2023-09-09-mlm_20230428_indobert_base_p2_001_en * Add model 2023-09-09-bodo_bert_mlm_base_article_en * Add model 2023-09-09-tiny_mlm_glue_cola_en * Add model 2023-09-09-bert_test_junzai_en * Add model 2023-09-09-bert_base_cnndm_en * Add model 2023-09-09-gww_en * Add model 2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6_en * Add model 2023-09-09-tiny_mlm_glue_qnli_en * Add model 2023-09-09-bert_funting_test_ai10_junzai_en * Add model 2023-09-09-tiny_mlm_glue_mnli_en * Add model 2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7_en * Add model 2023-09-09-tiny_mlm_glue_mrpc_en * Add model 2023-09-09-dal_bert_fa * Add model 2023-09-09-tiny_mlm_glue_qqp_en * Add model 2023-09-09-bert_patent_reference_extraction_en * Add model 2023-09-09-test_ru * Add model 2023-09-09-bert_finetuning_test_hug_en * Add model 2023-09-09-bert_base_pubmed_en * Add model 2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8_en * Add model 2023-09-09-bert_base_aeslc_kenkaneki_en * Add model 2023-09-09-absa_maskedlm_en --------- Co-authored-by: ahmedlone127 --------- Co-authored-by: jsl-models <74001263+jsl-models@users.noreply.github.com> Co-authored-by: ahmedlone127 --- .../2023-08-28-asr_whisper_tiny_opt_xx.md | 119 ++++++++++++++++++ ...23-09-07-579_stmodel_product_rem_v3a_en.md | 93 ++++++++++++++ .../2023-09-07-abstract_sim_query_en.md | 93 ++++++++++++++ .../2023-09-07-abstract_sim_sentence_en.md | 93 ++++++++++++++ ...09-07-action_policy_plans_classifier_en.md | 93 ++++++++++++++ ...023-09-07-all_datasets_v3_mpnet_base_en.md | 93 ++++++++++++++ ...023-09-07-all_datasets_v4_mpnet_base_en.md | 93 ++++++++++++++ .../2023-09-07-all_mpnet_base_v1_en.md | 93 ++++++++++++++ ...023-09-07-all_mpnet_base_v2_diptanuc_en.md | 93 ++++++++++++++ ...9-07-all_mpnet_base_v2_embedding_all_en.md | 93 ++++++++++++++ ..._base_v2_feature_extraction_pipeline_en.md | 93 ++++++++++++++ ...09-07-all_mpnet_base_v2_finetuned_v2_en.md | 93 ++++++++++++++ ...3-09-07-all_mpnet_base_v2_ftlegal_v3_en.md | 93 ++++++++++++++ ...2023-09-07-all_mpnet_base_v2_obrizum_en.md | 93 ++++++++++++++ ..._mpnet_base_v2_sentence_transformers_en.md | 93 ++++++++++++++ .../2023-09-07-all_mpnet_base_v2_table_en.md | 93 ++++++++++++++ ...l_mpnet_base_v2_tasky_classification_en.md | 93 ++++++++++++++ .../ahmedlone127/2023-09-07-attack_bert_en.md | 93 ++++++++++++++ ...biencoder_all_mpnet_base_v2_mmarcofr_fr.md | 93 ++++++++++++++ ..._multi_qa_mpnet_base_cos_v1_mmarcofr_fr.md | 93 ++++++++++++++ .../2023-09-07-biolord_stamb2_v1_en.md | 93 ++++++++++++++ ...9-07-burmese_awesome_setfit_model_98_en.md | 93 ++++++++++++++ ...3-09-07-burmese_awesome_setfit_model_en.md | 93 ++++++++++++++ .../2023-09-07-contradiction_psb_en.md | 93 ++++++++++++++ .../2023-09-07-contradiction_psb_lds_en.md | 93 ++++++++++++++ .../2023-09-07-covid_qa_mpnet_en.md | 93 ++++++++++++++ ...023-09-07-cpu_conditional_classifier_en.md | 93 ++++++++++++++ ...023-09-07-cpu_economywide_classifier_en.md | 93 ++++++++++++++ ...2023-09-07-cpu_mitigation_classifier_en.md | 93 ++++++++++++++ .../2023-09-07-cpu_netzero_classifier_en.md | 93 ++++++++++++++ ...3-09-07-cpu_transport_ghg_classifier_en.md | 93 ++++++++++++++ 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.../2023-09-07-java_expand_classifier_en.md | 93 ++++++++++++++ ...2023-09-07-java_ownership_classifier_en.md | 93 ++++++++++++++ .../2023-09-07-java_pointer_classifier_en.md | 93 ++++++++++++++ .../2023-09-07-java_rational_classifier_en.md | 93 ++++++++++++++ .../2023-09-07-java_summary_classifier_en.md | 93 ++++++++++++++ .../2023-09-07-java_usage_classifier_en.md | 93 ++++++++++++++ .../2023-09-07-keyphrase_mpnet_v1_en.md | 93 ++++++++++++++ ...09-07-kw_classification_setfit_model_en.md | 93 ++++++++++++++ ...7-kw_classification_setfithead_model_en.md | 93 ++++++++++++++ ...09-07-labels_per_job_title_fine_tune_en.md | 93 ++++++++++++++ ...net_adaptation_mitigation_classifier_en.md | 93 ++++++++++++++ .../2023-09-07-mpnet_base_articles_ner_en.md | 93 ++++++++++++++ .../2023-09-07-mpnet_base_snli_mnli_en.md | 93 ++++++++++++++ .../2023-09-07-mpnet_mnr_v2_fine_tuned_en.md | 93 ++++++++++++++ ...7-mpnet_multilabel_sector_classifier_en.md | 93 ++++++++++++++ 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b/docs/_posts/DevinTDHa/2023-08-28-asr_whisper_tiny_opt_xx.md @@ -0,0 +1,119 @@ +--- +layout: model +title: Official whisper-tiny Optimized +author: John Snow Labs +name: asr_whisper_tiny_opt +date: 2023-08-28 +tags: [whisper, audio, open_source, asr, onnx, xx] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Official pretrained Whisper model, adapted from HuggingFace transformer and curated to provide scalability and production-readiness using Spark NLP. + +This is a multilingual model and supports the following languages: + +Afrikaans, Arabic, Armenian, Azerbaijani, Belarusian, Bosnian, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, Galician, German, Greek, Hebrew, Hindi, Hungarian, Icelandic, Indonesian, Italian, Japanese, Kannada, Kazakh, Korean, Latvian, Lithuanian, Macedonian, Malay, Marathi, Maori, Nepali, Norwegian, Persian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovenian, Spanish, Swahili, Swedish, Tagalog, Tamil, Thai, Turkish, Ukrainian, Urdu, Vietnamese, and Welsh. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_opt_xx_5.1.1_3.0_1693213918398.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_opt_xx_5.1.1_3.0_1693213918398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +import sparknlp +from sparknlp.base import * +from sparknlp.annotator import * +from pyspark.ml import Pipeline + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_opt", "xx") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +processedAudioFloats = spark.createDataFrame([[rawFloats]]).toDF("audio_content") +result = pipeline.fit(processedAudioFloats).transform(processedAudioFloats) +result.select("text.result").show(truncate = False) +``` +```scala +import spark.implicits._ +import com.johnsnowlabs.nlp.base._ +import com.johnsnowlabs.nlp.annotators._ +import com.johnsnowlabs.nlp.annotators.audio.WhisperForCTC +import org.apache.spark.ml.Pipeline + +val audioAssembler: AudioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText: WhisperForCTC = WhisperForCTC + .pretrained("asr_whisper_tiny_opt", "xx") + .setInputCols("audio_assembler") + .setOutputCol("text") + +val pipeline: Pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val bufferedSource = + scala.io.Source.fromFile("src/test/resources/audio/txt/librispeech_asr_0.txt") + +val rawFloats = bufferedSource + .getLines() + .map(_.split(",").head.trim.toFloat) + .toArray +bufferedSource.close + +val processedAudioFloats = Seq(rawFloats).toDF("audio_content") + +val result = pipeline.fit(processedAudioFloats).transform(processedAudioFloats) +result.select("text.result").show(truncate = false) +``` +
+ +## Results + +```bash ++------------------------------------------------------------------------------------------------------------------------------------------------+ +|document | ++------------------------------------------------------------------------------------------------------------------------------------------------+ +|[{document, 0, 87, Mr. Quilter is the apostle of the middle classes and we are glad to welcome his gospel., {length -> 93680, audio -> 0}, []}]| ++------------------------------------------------------------------------------------------------------------------------------------------------+ +``` + +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_opt| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[document]| +|Language:|xx| +|Size:|239.3 MB| diff --git a/docs/_posts/ahmedlone127/2023-09-07-579_stmodel_product_rem_v3a_en.md b/docs/_posts/ahmedlone127/2023-09-07-579_stmodel_product_rem_v3a_en.md new file mode 100644 index 00000000000000..325e12c4529616 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-579_stmodel_product_rem_v3a_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English 579_stmodel_product_rem_v3a MPNetEmbeddings from jamiehudson +author: John Snow Labs +name: 579_stmodel_product_rem_v3a +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`579_stmodel_product_rem_v3a` is a English model originally trained by jamiehudson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/579_stmodel_product_rem_v3a_en_5.1.1_3.0_1694126614739.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/579_stmodel_product_rem_v3a_en_5.1.1_3.0_1694126614739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("579_stmodel_product_rem_v3a","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("579_stmodel_product_rem_v3a", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|579_stmodel_product_rem_v3a| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/jamiehudson/579-STmodel-product-rem-v3a \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-abstract_sim_query_en.md b/docs/_posts/ahmedlone127/2023-09-07-abstract_sim_query_en.md new file mode 100644 index 00000000000000..6bbdf8e11a679c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-abstract_sim_query_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English abstract_sim_query MPNetEmbeddings from biu-nlp +author: John Snow Labs +name: abstract_sim_query +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`abstract_sim_query` is a English model originally trained by biu-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/abstract_sim_query_en_5.1.1_3.0_1694125761744.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/abstract_sim_query_en_5.1.1_3.0_1694125761744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("abstract_sim_query","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("abstract_sim_query", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|abstract_sim_query| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/biu-nlp/abstract-sim-query \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-abstract_sim_sentence_en.md b/docs/_posts/ahmedlone127/2023-09-07-abstract_sim_sentence_en.md new file mode 100644 index 00000000000000..49fe8380319cca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-abstract_sim_sentence_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English abstract_sim_sentence MPNetEmbeddings from biu-nlp +author: John Snow Labs +name: abstract_sim_sentence +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`abstract_sim_sentence` is a English model originally trained by biu-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/abstract_sim_sentence_en_5.1.1_3.0_1694129808816.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/abstract_sim_sentence_en_5.1.1_3.0_1694129808816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("abstract_sim_sentence","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("abstract_sim_sentence", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|abstract_sim_sentence| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/biu-nlp/abstract-sim-sentence \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-action_policy_plans_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-action_policy_plans_classifier_en.md new file mode 100644 index 00000000000000..7cc9b8271e4686 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-action_policy_plans_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English action_policy_plans_classifier MPNetEmbeddings from ppsingh +author: John Snow Labs +name: action_policy_plans_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`action_policy_plans_classifier` is a English model originally trained by ppsingh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/action_policy_plans_classifier_en_5.1.1_3.0_1694128081191.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/action_policy_plans_classifier_en_5.1.1_3.0_1694128081191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("action_policy_plans_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("action_policy_plans_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|action_policy_plans_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/ppsingh/action-policy-plans-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_datasets_v3_mpnet_base_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_datasets_v3_mpnet_base_en.md new file mode 100644 index 00000000000000..4699e31ffc1bdf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_datasets_v3_mpnet_base_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_datasets_v3_mpnet_base Mpnet from flax-sentence-embeddings +author: John Snow Labs +name: all_datasets_v3_mpnet_base +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_datasets_v3_mpnet_base` is a English model originally trained by flax-sentence-embeddings. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_datasets_v3_mpnet_base_en_5.1.1_3.0_1694122685945.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_datasets_v3_mpnet_base_en_5.1.1_3.0_1694122685945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_datasets_v3_mpnet_base","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_datasets_v3_mpnet_base", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_datasets_v3_mpnet_base| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/flax-sentence-embeddings/all_datasets_v3_mpnet-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_datasets_v4_mpnet_base_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_datasets_v4_mpnet_base_en.md new file mode 100644 index 00000000000000..e21e755b634864 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_datasets_v4_mpnet_base_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_datasets_v4_mpnet_base Mpnet from flax-sentence-embeddings +author: John Snow Labs +name: all_datasets_v4_mpnet_base +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_datasets_v4_mpnet_base` is a English model originally trained by flax-sentence-embeddings. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_datasets_v4_mpnet_base_en_5.1.1_3.0_1694122798617.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_datasets_v4_mpnet_base_en_5.1.1_3.0_1694122798617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_datasets_v4_mpnet_base","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_datasets_v4_mpnet_base", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_datasets_v4_mpnet_base| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/flax-sentence-embeddings/all_datasets_v4_mpnet-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v1_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v1_en.md new file mode 100644 index 00000000000000..ce015e01ebd9ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v1 MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: all_mpnet_base_v1 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v1` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v1_en_5.1.1_3.0_1694125007752.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v1_en_5.1.1_3.0_1694125007752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v1","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v1", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/sentence-transformers/all-mpnet-base-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_diptanuc_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_diptanuc_en.md new file mode 100644 index 00000000000000..f133d854b1df83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_diptanuc_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_diptanuc MPNetEmbeddings from diptanuc +author: John Snow Labs +name: all_mpnet_base_v2_diptanuc +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_diptanuc` is a English model originally trained by diptanuc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_diptanuc_en_5.1.1_3.0_1694128964381.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_diptanuc_en_5.1.1_3.0_1694128964381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_diptanuc","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_diptanuc", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_diptanuc| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/diptanuc/all-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_embedding_all_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_embedding_all_en.md new file mode 100644 index 00000000000000..d5c2b27c9b6958 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_embedding_all_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_embedding_all MPNetEmbeddings from LLukas22 +author: John Snow Labs +name: all_mpnet_base_v2_embedding_all +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_embedding_all` is a English model originally trained by LLukas22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_embedding_all_en_5.1.1_3.0_1694127834094.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_embedding_all_en_5.1.1_3.0_1694127834094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_embedding_all","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_embedding_all", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_embedding_all| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.4 MB| + +## References + +https://huggingface.co/LLukas22/all-mpnet-base-v2-embedding-all \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_feature_extraction_pipeline_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_feature_extraction_pipeline_en.md new file mode 100644 index 00000000000000..ae366dffd48011 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_feature_extraction_pipeline_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_feature_extraction_pipeline MPNetEmbeddings from questgen +author: John Snow Labs +name: all_mpnet_base_v2_feature_extraction_pipeline +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_feature_extraction_pipeline` is a English model originally trained by questgen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_feature_extraction_pipeline_en_5.1.1_3.0_1694130976472.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_feature_extraction_pipeline_en_5.1.1_3.0_1694130976472.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_feature_extraction_pipeline","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_feature_extraction_pipeline", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_feature_extraction_pipeline| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/questgen/all-mpnet-base-v2-feature-extraction-pipeline \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_finetuned_v2_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_finetuned_v2_en.md new file mode 100644 index 00000000000000..51d5bcfe605c3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_finetuned_v2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_finetuned_v2 MPNetEmbeddings from Humair +author: John Snow Labs +name: all_mpnet_base_v2_finetuned_v2 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_finetuned_v2` is a English model originally trained by Humair. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_finetuned_v2_en_5.1.1_3.0_1694127987280.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_finetuned_v2_en_5.1.1_3.0_1694127987280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_finetuned_v2","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_finetuned_v2", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_finetuned_v2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/Humair/all-mpnet-base-v2-finetuned-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_ftlegal_v3_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_ftlegal_v3_en.md new file mode 100644 index 00000000000000..a9b240367cd983 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_ftlegal_v3_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_ftlegal_v3 MPNetEmbeddings from sukantan +author: John Snow Labs +name: all_mpnet_base_v2_ftlegal_v3 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_ftlegal_v3` is a English model originally trained by sukantan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_ftlegal_v3_en_5.1.1_3.0_1694124734019.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_ftlegal_v3_en_5.1.1_3.0_1694124734019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_ftlegal_v3","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_ftlegal_v3", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_ftlegal_v3| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/sukantan/all-mpnet-base-v2-ftlegal-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_obrizum_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_obrizum_en.md new file mode 100644 index 00000000000000..32f233253f2c5b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_obrizum_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_obrizum MPNetEmbeddings from obrizum +author: John Snow Labs +name: all_mpnet_base_v2_obrizum +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_obrizum` is a English model originally trained by obrizum. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_obrizum_en_5.1.1_3.0_1694126818034.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_obrizum_en_5.1.1_3.0_1694126818034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_obrizum","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_obrizum", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_obrizum| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/obrizum/all-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_sentence_transformers_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_sentence_transformers_en.md new file mode 100644 index 00000000000000..f2c147c23ecf65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_sentence_transformers_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_sentence_transformers MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: all_mpnet_base_v2_sentence_transformers +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_sentence_transformers` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_sentence_transformers_en_5.1.1_3.0_1694125144698.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_sentence_transformers_en_5.1.1_3.0_1694125144698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_sentence_transformers","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_sentence_transformers", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_sentence_transformers| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/sentence-transformers/all-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_table_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_table_en.md new file mode 100644 index 00000000000000..cedd3ff4fe0785 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_table_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_table MPNetEmbeddings from deepset +author: John Snow Labs +name: all_mpnet_base_v2_table +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_table` is a English model originally trained by deepset. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_table_en_5.1.1_3.0_1694130760725.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_table_en_5.1.1_3.0_1694130760725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_table","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_table", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_table| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/deepset/all-mpnet-base-v2-table \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_tasky_classification_en.md b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_tasky_classification_en.md new file mode 100644 index 00000000000000..2cfb997b9a8fef --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-all_mpnet_base_v2_tasky_classification_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_tasky_classification MPNetEmbeddings from khalidalt +author: John Snow Labs +name: all_mpnet_base_v2_tasky_classification +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_tasky_classification` is a English model originally trained by khalidalt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_tasky_classification_en_5.1.1_3.0_1694127102096.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_tasky_classification_en_5.1.1_3.0_1694127102096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_tasky_classification","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_tasky_classification", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_tasky_classification| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.4 MB| + +## References + +https://huggingface.co/khalidalt/all-mpnet-base-v2-tasky-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-attack_bert_en.md b/docs/_posts/ahmedlone127/2023-09-07-attack_bert_en.md new file mode 100644 index 00000000000000..f13570be2518c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-attack_bert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English attack_bert MPNetEmbeddings from basel +author: John Snow Labs +name: attack_bert +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`attack_bert` is a English model originally trained by basel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/attack_bert_en_5.1.1_3.0_1694128690149.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/attack_bert_en_5.1.1_3.0_1694128690149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("attack_bert","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("attack_bert", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|attack_bert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/basel/ATTACK-BERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-biencoder_all_mpnet_base_v2_mmarcofr_fr.md b/docs/_posts/ahmedlone127/2023-09-07-biencoder_all_mpnet_base_v2_mmarcofr_fr.md new file mode 100644 index 00000000000000..982fcfb9070a33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-biencoder_all_mpnet_base_v2_mmarcofr_fr.md @@ -0,0 +1,93 @@ +--- +layout: model +title: French biencoder_all_mpnet_base_v2_mmarcofr MPNetEmbeddings from antoinelouis +author: John Snow Labs +name: biencoder_all_mpnet_base_v2_mmarcofr +date: 2023-09-07 +tags: [mpnet, fr, open_source, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biencoder_all_mpnet_base_v2_mmarcofr` is a French model originally trained by antoinelouis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biencoder_all_mpnet_base_v2_mmarcofr_fr_5.1.1_3.0_1694130385847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biencoder_all_mpnet_base_v2_mmarcofr_fr_5.1.1_3.0_1694130385847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("biencoder_all_mpnet_base_v2_mmarcofr","fr") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("biencoder_all_mpnet_base_v2_mmarcofr", "fr") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biencoder_all_mpnet_base_v2_mmarcofr| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|fr| +|Size:|406.8 MB| + +## References + +https://huggingface.co/antoinelouis/biencoder-all-mpnet-base-v2-mmarcoFR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr_fr.md b/docs/_posts/ahmedlone127/2023-09-07-biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr_fr.md new file mode 100644 index 00000000000000..76e704412ad457 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr_fr.md @@ -0,0 +1,93 @@ +--- +layout: model +title: French biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr MPNetEmbeddings from antoinelouis +author: John Snow Labs +name: biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr +date: 2023-09-07 +tags: [mpnet, fr, open_source, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr` is a French model originally trained by antoinelouis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr_fr_5.1.1_3.0_1694130498418.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr_fr_5.1.1_3.0_1694130498418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr","fr") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr", "fr") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biencoder_multi_qa_mpnet_base_cos_v1_mmarcofr| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|fr| +|Size:|407.0 MB| + +## References + +https://huggingface.co/antoinelouis/biencoder-multi-qa-mpnet-base-cos-v1-mmarcoFR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-biolord_stamb2_v1_en.md b/docs/_posts/ahmedlone127/2023-09-07-biolord_stamb2_v1_en.md new file mode 100644 index 00000000000000..123df34811969b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-biolord_stamb2_v1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English biolord_stamb2_v1 MPNetEmbeddings from FremyCompany +author: John Snow Labs +name: biolord_stamb2_v1 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biolord_stamb2_v1` is a English model originally trained by FremyCompany. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biolord_stamb2_v1_en_5.1.1_3.0_1694129274443.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biolord_stamb2_v1_en_5.1.1_3.0_1694129274443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("biolord_stamb2_v1","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("biolord_stamb2_v1", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biolord_stamb2_v1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/FremyCompany/BioLORD-STAMB2-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-burmese_awesome_setfit_model_98_en.md b/docs/_posts/ahmedlone127/2023-09-07-burmese_awesome_setfit_model_98_en.md new file mode 100644 index 00000000000000..377f64e866450c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-burmese_awesome_setfit_model_98_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English burmese_awesome_setfit_model_98 MPNetEmbeddings from lewtun +author: John Snow Labs +name: burmese_awesome_setfit_model_98 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_98` is a English model originally trained by lewtun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_98_en_5.1.1_3.0_1694129129625.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_98_en_5.1.1_3.0_1694129129625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_98","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("burmese_awesome_setfit_model_98", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_setfit_model_98| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/lewtun/my-awesome-setfit-model-98 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-burmese_awesome_setfit_model_en.md b/docs/_posts/ahmedlone127/2023-09-07-burmese_awesome_setfit_model_en.md new file mode 100644 index 00000000000000..42388f7b246af7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-burmese_awesome_setfit_model_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English burmese_awesome_setfit_model MPNetEmbeddings from lewtun +author: John Snow Labs +name: burmese_awesome_setfit_model +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model` is a English model originally trained by lewtun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_en_5.1.1_3.0_1694127834027.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_en_5.1.1_3.0_1694127834027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("burmese_awesome_setfit_model","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("burmese_awesome_setfit_model", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_setfit_model| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/lewtun/my-awesome-setfit-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-contradiction_psb_en.md b/docs/_posts/ahmedlone127/2023-09-07-contradiction_psb_en.md new file mode 100644 index 00000000000000..d1db94ad324572 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-contradiction_psb_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English contradiction_psb MPNetEmbeddings from nategro +author: John Snow Labs +name: contradiction_psb +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`contradiction_psb` is a English model originally trained by nategro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/contradiction_psb_en_5.1.1_3.0_1694128728540.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/contradiction_psb_en_5.1.1_3.0_1694128728540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("contradiction_psb","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("contradiction_psb", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|contradiction_psb| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/nategro/contradiction-psb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-contradiction_psb_lds_en.md b/docs/_posts/ahmedlone127/2023-09-07-contradiction_psb_lds_en.md new file mode 100644 index 00000000000000..8ef8e3718e712d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-contradiction_psb_lds_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English contradiction_psb_lds MPNetEmbeddings from nategro +author: John Snow Labs +name: contradiction_psb_lds +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`contradiction_psb_lds` is a English model originally trained by nategro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/contradiction_psb_lds_en_5.1.1_3.0_1694128518758.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/contradiction_psb_lds_en_5.1.1_3.0_1694128518758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("contradiction_psb_lds","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("contradiction_psb_lds", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|contradiction_psb_lds| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/nategro/contradiction-psb-lds \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-covid_qa_mpnet_en.md b/docs/_posts/ahmedlone127/2023-09-07-covid_qa_mpnet_en.md new file mode 100644 index 00000000000000..2e0f935954e05a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-covid_qa_mpnet_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English covid_qa_mpnet MPNetEmbeddings from shaina +author: John Snow Labs +name: covid_qa_mpnet +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_qa_mpnet` is a English model originally trained by shaina. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_qa_mpnet_en_5.1.1_3.0_1694130190650.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_qa_mpnet_en_5.1.1_3.0_1694130190650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("covid_qa_mpnet","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("covid_qa_mpnet", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_qa_mpnet| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|399.6 MB| + +## References + +https://huggingface.co/shaina/covid_qa_mpnet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-cpu_conditional_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-cpu_conditional_classifier_en.md new file mode 100644 index 00000000000000..bbb2c1fa2a7a50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-cpu_conditional_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English cpu_conditional_classifier MPNetEmbeddings from mtyrrell +author: John Snow Labs +name: cpu_conditional_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cpu_conditional_classifier` is a English model originally trained by mtyrrell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cpu_conditional_classifier_en_5.1.1_3.0_1694130906627.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cpu_conditional_classifier_en_5.1.1_3.0_1694130906627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("cpu_conditional_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("cpu_conditional_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cpu_conditional_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/mtyrrell/CPU_Conditional_Classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-cpu_economywide_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-cpu_economywide_classifier_en.md new file mode 100644 index 00000000000000..ab6ce4e6371e5a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-cpu_economywide_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English cpu_economywide_classifier MPNetEmbeddings from mtyrrell +author: John Snow Labs +name: cpu_economywide_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cpu_economywide_classifier` is a English model originally trained by mtyrrell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cpu_economywide_classifier_en_5.1.1_3.0_1694126286182.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cpu_economywide_classifier_en_5.1.1_3.0_1694126286182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("cpu_economywide_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("cpu_economywide_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cpu_economywide_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/mtyrrell/CPU_Economywide_Classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-cpu_mitigation_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-cpu_mitigation_classifier_en.md new file mode 100644 index 00000000000000..2b633a79c6b1a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-cpu_mitigation_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English cpu_mitigation_classifier MPNetEmbeddings from mtyrrell +author: John Snow Labs +name: cpu_mitigation_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cpu_mitigation_classifier` is a English model originally trained by mtyrrell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cpu_mitigation_classifier_en_5.1.1_3.0_1694131013907.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cpu_mitigation_classifier_en_5.1.1_3.0_1694131013907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("cpu_mitigation_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("cpu_mitigation_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cpu_mitigation_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/mtyrrell/CPU_Mitigation_Classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-cpu_netzero_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-cpu_netzero_classifier_en.md new file mode 100644 index 00000000000000..7e781c7f21a043 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-cpu_netzero_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English cpu_netzero_classifier MPNetEmbeddings from mtyrrell +author: John Snow Labs +name: cpu_netzero_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cpu_netzero_classifier` is a English model originally trained by mtyrrell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cpu_netzero_classifier_en_5.1.1_3.0_1694130812400.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cpu_netzero_classifier_en_5.1.1_3.0_1694130812400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("cpu_netzero_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("cpu_netzero_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cpu_netzero_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/mtyrrell/CPU_Netzero_Classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-cpu_transport_ghg_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-cpu_transport_ghg_classifier_en.md new file mode 100644 index 00000000000000..aa734b59a7da3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-cpu_transport_ghg_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English cpu_transport_ghg_classifier MPNetEmbeddings from mtyrrell +author: John Snow Labs +name: cpu_transport_ghg_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cpu_transport_ghg_classifier` is a English model originally trained by mtyrrell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cpu_transport_ghg_classifier_en_5.1.1_3.0_1694130718368.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cpu_transport_ghg_classifier_en_5.1.1_3.0_1694130718368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("cpu_transport_ghg_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("cpu_transport_ghg_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cpu_transport_ghg_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/mtyrrell/CPU_Transport_GHG_Classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en.md b/docs/_posts/ahmedlone127/2023-09-07-cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en.md new file mode 100644 index 00000000000000..a401539251dd4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average MPNetEmbeddings from teven +author: John Snow Labs +name: cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average` is a English model originally trained by teven. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en_5.1.1_3.0_1694128061507.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average_en_5.1.1_3.0_1694128061507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cross_all_mpnet_base_v2_finetuned_webnlg2020_metric_average| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/teven/cross_all-mpnet-base-v2_finetuned_WebNLG2020_metric_average \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-domainadaptm2_en.md b/docs/_posts/ahmedlone127/2023-09-07-domainadaptm2_en.md new file mode 100644 index 00000000000000..3cc6a1ea64e449 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-domainadaptm2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English domainadaptm2 MPNetEmbeddings from dani0f +author: John Snow Labs +name: domainadaptm2 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`domainadaptm2` is a English model originally trained by dani0f. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/domainadaptm2_en_5.1.1_3.0_1694128846142.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/domainadaptm2_en_5.1.1_3.0_1694128846142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("domainadaptm2","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("domainadaptm2", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|domainadaptm2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/dani0f/DomainAdaptM2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-due_eshop_21_en.md b/docs/_posts/ahmedlone127/2023-09-07-due_eshop_21_en.md new file mode 100644 index 00000000000000..d304bf7e478a68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-due_eshop_21_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English due_eshop_21 MPNetEmbeddings from konverner +author: John Snow Labs +name: due_eshop_21 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`due_eshop_21` is a English model originally trained by konverner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/due_eshop_21_en_5.1.1_3.0_1694129070639.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/due_eshop_21_en_5.1.1_3.0_1694129070639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("due_eshop_21","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("due_eshop_21", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|due_eshop_21| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/konverner/due_eshop_21 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-due_eshop_21_multilabel_en.md b/docs/_posts/ahmedlone127/2023-09-07-due_eshop_21_multilabel_en.md new file mode 100644 index 00000000000000..053dc4674455fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-due_eshop_21_multilabel_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English due_eshop_21_multilabel MPNetEmbeddings from konverner +author: John Snow Labs +name: due_eshop_21_multilabel +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`due_eshop_21_multilabel` is a English model originally trained by konverner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/due_eshop_21_multilabel_en_5.1.1_3.0_1694129883699.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/due_eshop_21_multilabel_en_5.1.1_3.0_1694129883699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("due_eshop_21_multilabel","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("due_eshop_21_multilabel", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|due_eshop_21_multilabel| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/konverner/due_eshop_21_multilabel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-due_retail_25_en.md b/docs/_posts/ahmedlone127/2023-09-07-due_retail_25_en.md new file mode 100644 index 00000000000000..8b96c7c057aea2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-due_retail_25_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English due_retail_25 MPNetEmbeddings from konverner +author: John Snow Labs +name: due_retail_25 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`due_retail_25` is a English model originally trained by konverner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/due_retail_25_en_5.1.1_3.0_1694129177106.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/due_retail_25_en_5.1.1_3.0_1694129177106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("due_retail_25","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("due_retail_25", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|due_retail_25| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/konverner/due_retail_25 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-ecolo_pas_ecolo_v0.1_en.md b/docs/_posts/ahmedlone127/2023-09-07-ecolo_pas_ecolo_v0.1_en.md new file mode 100644 index 00000000000000..18274be1cdf58e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-ecolo_pas_ecolo_v0.1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English ecolo_pas_ecolo_v0.1 MPNetEmbeddings from eclaircies +author: John Snow Labs +name: ecolo_pas_ecolo_v0.1 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ecolo_pas_ecolo_v0.1` is a English model originally trained by eclaircies. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ecolo_pas_ecolo_v0.1_en_5.1.1_3.0_1694127982409.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ecolo_pas_ecolo_v0.1_en_5.1.1_3.0_1694127982409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("ecolo_pas_ecolo_v0.1","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("ecolo_pas_ecolo_v0.1", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ecolo_pas_ecolo_v0.1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/eclaircies/ecolo-pas-ecolo-v0.1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-fail_detect_en.md b/docs/_posts/ahmedlone127/2023-09-07-fail_detect_en.md new file mode 100644 index 00000000000000..5aacab8cac61e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-fail_detect_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English fail_detect MPNetEmbeddings from Ngit +author: John Snow Labs +name: fail_detect +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fail_detect` is a English model originally trained by Ngit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fail_detect_en_5.1.1_3.0_1694130543509.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fail_detect_en_5.1.1_3.0_1694130543509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("fail_detect","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("fail_detect", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fail_detect| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/Ngit/fail-detect \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-fewshotissueclassifier_nlbse23_en.md b/docs/_posts/ahmedlone127/2023-09-07-fewshotissueclassifier_nlbse23_en.md new file mode 100644 index 00000000000000..0e3ddeef0052d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-fewshotissueclassifier_nlbse23_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English fewshotissueclassifier_nlbse23 MPNetEmbeddings from PeppoCola +author: John Snow Labs +name: fewshotissueclassifier_nlbse23 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fewshotissueclassifier_nlbse23` is a English model originally trained by PeppoCola. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fewshotissueclassifier_nlbse23_en_5.1.1_3.0_1694123644544.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fewshotissueclassifier_nlbse23_en_5.1.1_3.0_1694123644544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("fewshotissueclassifier_nlbse23","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("fewshotissueclassifier_nlbse23", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fewshotissueclassifier_nlbse23| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/PeppoCola/FewShotIssueClassifier-NLBSE23 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-github_issues_mpnet_southern_sotho_e10_en.md b/docs/_posts/ahmedlone127/2023-09-07-github_issues_mpnet_southern_sotho_e10_en.md new file mode 100644 index 00000000000000..44ed625f04aa40 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-github_issues_mpnet_southern_sotho_e10_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English github_issues_mpnet_southern_sotho_e10 MPNetEmbeddings from Collab-uniba +author: John Snow Labs +name: github_issues_mpnet_southern_sotho_e10 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`github_issues_mpnet_southern_sotho_e10` is a English model originally trained by Collab-uniba. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/github_issues_mpnet_southern_sotho_e10_en_5.1.1_3.0_1694124363662.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/github_issues_mpnet_southern_sotho_e10_en_5.1.1_3.0_1694124363662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("github_issues_mpnet_southern_sotho_e10","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("github_issues_mpnet_southern_sotho_e10", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|github_issues_mpnet_southern_sotho_e10| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.4 MB| + +## References + +https://huggingface.co/Collab-uniba/github-issues-mpnet-st-e10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-github_issues_preprocessed_mpnet_southern_sotho_e10_en.md b/docs/_posts/ahmedlone127/2023-09-07-github_issues_preprocessed_mpnet_southern_sotho_e10_en.md new file mode 100644 index 00000000000000..a8dbdfc2bc8a7f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-github_issues_preprocessed_mpnet_southern_sotho_e10_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English github_issues_preprocessed_mpnet_southern_sotho_e10 MPNetEmbeddings from Collab-uniba +author: John Snow Labs +name: github_issues_preprocessed_mpnet_southern_sotho_e10 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`github_issues_preprocessed_mpnet_southern_sotho_e10` is a English model originally trained by Collab-uniba. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/github_issues_preprocessed_mpnet_southern_sotho_e10_en_5.1.1_3.0_1694129779112.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/github_issues_preprocessed_mpnet_southern_sotho_e10_en_5.1.1_3.0_1694129779112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("github_issues_preprocessed_mpnet_southern_sotho_e10","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("github_issues_preprocessed_mpnet_southern_sotho_e10", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|github_issues_preprocessed_mpnet_southern_sotho_e10| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/Collab-uniba/github-issues-preprocessed-mpnet-st-e10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-ikitracs_conditional_en.md b/docs/_posts/ahmedlone127/2023-09-07-ikitracs_conditional_en.md new file mode 100644 index 00000000000000..5cad8e5a032055 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-ikitracs_conditional_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English ikitracs_conditional MPNetEmbeddings from ilaria-oneofftech +author: John Snow Labs +name: ikitracs_conditional +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ikitracs_conditional` is a English model originally trained by ilaria-oneofftech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ikitracs_conditional_en_5.1.1_3.0_1694128507701.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ikitracs_conditional_en_5.1.1_3.0_1694128507701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("ikitracs_conditional","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("ikitracs_conditional", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ikitracs_conditional| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/ilaria-oneofftech/ikitracs_conditional \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-ikitracs_mitigation_en.md b/docs/_posts/ahmedlone127/2023-09-07-ikitracs_mitigation_en.md new file mode 100644 index 00000000000000..0afa0e64224f18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-ikitracs_mitigation_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English ikitracs_mitigation MPNetEmbeddings from ilaria-oneofftech +author: John Snow Labs +name: ikitracs_mitigation +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ikitracs_mitigation` is a English model originally trained by ilaria-oneofftech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ikitracs_mitigation_en_5.1.1_3.0_1694131004753.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ikitracs_mitigation_en_5.1.1_3.0_1694131004753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("ikitracs_mitigation","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("ikitracs_mitigation", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ikitracs_mitigation| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/ilaria-oneofftech/ikitracs_mitigation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-initial_model_en.md b/docs/_posts/ahmedlone127/2023-09-07-initial_model_en.md new file mode 100644 index 00000000000000..5ed4ec5f6a2209 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-initial_model_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English initial_model MPNetEmbeddings from ishan +author: John Snow Labs +name: initial_model +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`initial_model` is a English model originally trained by ishan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/initial_model_en_5.1.1_3.0_1694130168927.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/initial_model_en_5.1.1_3.0_1694130168927.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("initial_model","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("initial_model", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|initial_model| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/ishan/initial-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-initial_model_v3_en.md b/docs/_posts/ahmedlone127/2023-09-07-initial_model_v3_en.md new file mode 100644 index 00000000000000..129c0440d2676e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-initial_model_v3_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English initial_model_v3 MPNetEmbeddings from ishan +author: John Snow Labs +name: initial_model_v3 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`initial_model_v3` is a English model originally trained by ishan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/initial_model_v3_en_5.1.1_3.0_1694129994652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/initial_model_v3_en_5.1.1_3.0_1694129994652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("initial_model_v3","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("initial_model_v3", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|initial_model_v3| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/ishan/initial-model-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-invoiceornot_en.md b/docs/_posts/ahmedlone127/2023-09-07-invoiceornot_en.md new file mode 100644 index 00000000000000..c0bc8dd3f777c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-invoiceornot_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English invoiceornot MPNetEmbeddings from HamzaFarhan +author: John Snow Labs +name: invoiceornot +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`invoiceornot` is a English model originally trained by HamzaFarhan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/invoiceornot_en_5.1.1_3.0_1694130618615.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/invoiceornot_en_5.1.1_3.0_1694130618615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("invoiceornot","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("invoiceornot", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|invoiceornot| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/HamzaFarhan/InvoiceOrNot \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-java_deprecation_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-java_deprecation_classifier_en.md new file mode 100644 index 00000000000000..880837685563ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-java_deprecation_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English java_deprecation_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: java_deprecation_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`java_deprecation_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/java_deprecation_classifier_en_5.1.1_3.0_1694129093936.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/java_deprecation_classifier_en_5.1.1_3.0_1694129093936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("java_deprecation_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("java_deprecation_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|java_deprecation_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/AISE-TUDelft/java-deprecation-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-java_expand_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-java_expand_classifier_en.md new file mode 100644 index 00000000000000..337820017573dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-java_expand_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English java_expand_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: java_expand_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`java_expand_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/java_expand_classifier_en_5.1.1_3.0_1694125429009.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/java_expand_classifier_en_5.1.1_3.0_1694125429009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("java_expand_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("java_expand_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|java_expand_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/AISE-TUDelft/java-expand-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-java_ownership_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-java_ownership_classifier_en.md new file mode 100644 index 00000000000000..7c796181e1faf9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-java_ownership_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English java_ownership_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: java_ownership_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`java_ownership_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/java_ownership_classifier_en_5.1.1_3.0_1694130489843.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/java_ownership_classifier_en_5.1.1_3.0_1694130489843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("java_ownership_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("java_ownership_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|java_ownership_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/AISE-TUDelft/java-ownership-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-java_pointer_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-java_pointer_classifier_en.md new file mode 100644 index 00000000000000..482aebd6760291 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-java_pointer_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English java_pointer_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: java_pointer_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`java_pointer_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/java_pointer_classifier_en_5.1.1_3.0_1694129302252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/java_pointer_classifier_en_5.1.1_3.0_1694129302252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("java_pointer_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("java_pointer_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|java_pointer_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/AISE-TUDelft/java-pointer-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-java_rational_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-java_rational_classifier_en.md new file mode 100644 index 00000000000000..075adffa3773b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-java_rational_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English java_rational_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: java_rational_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`java_rational_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/java_rational_classifier_en_5.1.1_3.0_1694129985001.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/java_rational_classifier_en_5.1.1_3.0_1694129985001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("java_rational_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("java_rational_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|java_rational_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/AISE-TUDelft/java-rational-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-java_summary_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-java_summary_classifier_en.md new file mode 100644 index 00000000000000..df5e665a2400e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-java_summary_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English java_summary_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: java_summary_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`java_summary_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/java_summary_classifier_en_5.1.1_3.0_1694129191538.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/java_summary_classifier_en_5.1.1_3.0_1694129191538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("java_summary_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("java_summary_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|java_summary_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/AISE-TUDelft/java-summary-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-java_usage_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-java_usage_classifier_en.md new file mode 100644 index 00000000000000..fdbc91bb5ca310 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-java_usage_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English java_usage_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: java_usage_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`java_usage_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/java_usage_classifier_en_5.1.1_3.0_1694129416711.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/java_usage_classifier_en_5.1.1_3.0_1694129416711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("java_usage_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("java_usage_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|java_usage_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/AISE-TUDelft/java-usage-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-keyphrase_mpnet_v1_en.md b/docs/_posts/ahmedlone127/2023-09-07-keyphrase_mpnet_v1_en.md new file mode 100644 index 00000000000000..65fa2878f9c90a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-keyphrase_mpnet_v1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English keyphrase_mpnet_v1 MPNetEmbeddings from uclanlp +author: John Snow Labs +name: keyphrase_mpnet_v1 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keyphrase_mpnet_v1` is a English model originally trained by uclanlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keyphrase_mpnet_v1_en_5.1.1_3.0_1694129569189.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keyphrase_mpnet_v1_en_5.1.1_3.0_1694129569189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("keyphrase_mpnet_v1","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("keyphrase_mpnet_v1", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|keyphrase_mpnet_v1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/uclanlp/keyphrase-mpnet-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-kw_classification_setfit_model_en.md b/docs/_posts/ahmedlone127/2023-09-07-kw_classification_setfit_model_en.md new file mode 100644 index 00000000000000..b812624251d9b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-kw_classification_setfit_model_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kw_classification_setfit_model MPNetEmbeddings from gyuri2020 +author: John Snow Labs +name: kw_classification_setfit_model +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kw_classification_setfit_model` is a English model originally trained by gyuri2020. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kw_classification_setfit_model_en_5.1.1_3.0_1694126154625.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kw_classification_setfit_model_en_5.1.1_3.0_1694126154625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("kw_classification_setfit_model","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("kw_classification_setfit_model", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kw_classification_setfit_model| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/gyuri2020/kw-classification-setfit-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-kw_classification_setfithead_model_en.md b/docs/_posts/ahmedlone127/2023-09-07-kw_classification_setfithead_model_en.md new file mode 100644 index 00000000000000..1543ab64238696 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-kw_classification_setfithead_model_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kw_classification_setfithead_model MPNetEmbeddings from gyuri2020 +author: John Snow Labs +name: kw_classification_setfithead_model +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kw_classification_setfithead_model` is a English model originally trained by gyuri2020. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kw_classification_setfithead_model_en_5.1.1_3.0_1694126415270.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kw_classification_setfithead_model_en_5.1.1_3.0_1694126415270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("kw_classification_setfithead_model","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("kw_classification_setfithead_model", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kw_classification_setfithead_model| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/gyuri2020/kw-classification-setfithead-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-labels_per_job_title_fine_tune_en.md b/docs/_posts/ahmedlone127/2023-09-07-labels_per_job_title_fine_tune_en.md new file mode 100644 index 00000000000000..483cb814171b35 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-labels_per_job_title_fine_tune_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English labels_per_job_title_fine_tune MPNetEmbeddings from marianodo +author: John Snow Labs +name: labels_per_job_title_fine_tune +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`labels_per_job_title_fine_tune` is a English model originally trained by marianodo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/labels_per_job_title_fine_tune_en_5.1.1_3.0_1694129285422.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/labels_per_job_title_fine_tune_en_5.1.1_3.0_1694129285422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("labels_per_job_title_fine_tune","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("labels_per_job_title_fine_tune", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|labels_per_job_title_fine_tune| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/marianodo/labels-per-job-title-fine-tune \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-mpnet_adaptation_mitigation_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-mpnet_adaptation_mitigation_classifier_en.md new file mode 100644 index 00000000000000..adb7e3c51ab6be --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-mpnet_adaptation_mitigation_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mpnet_adaptation_mitigation_classifier MPNetEmbeddings from ppsingh +author: John Snow Labs +name: mpnet_adaptation_mitigation_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_adaptation_mitigation_classifier` is a English model originally trained by ppsingh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_adaptation_mitigation_classifier_en_5.1.1_3.0_1694124441818.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_adaptation_mitigation_classifier_en_5.1.1_3.0_1694124441818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("mpnet_adaptation_mitigation_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("mpnet_adaptation_mitigation_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_adaptation_mitigation_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/ppsingh/mpnet-adaptation_mitigation-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-mpnet_base_articles_ner_en.md b/docs/_posts/ahmedlone127/2023-09-07-mpnet_base_articles_ner_en.md new file mode 100644 index 00000000000000..d0cb6906753584 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-mpnet_base_articles_ner_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mpnet_base_articles_ner MPNetEmbeddings from evangeliazve +author: John Snow Labs +name: mpnet_base_articles_ner +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_articles_ner` is a English model originally trained by evangeliazve. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_articles_ner_en_5.1.1_3.0_1694130444573.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_articles_ner_en_5.1.1_3.0_1694130444573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("mpnet_base_articles_ner","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("mpnet_base_articles_ner", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_articles_ner| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|382.8 MB| + +## References + +https://huggingface.co/evangeliazve/mpnet-base-articles-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-mpnet_base_snli_mnli_en.md b/docs/_posts/ahmedlone127/2023-09-07-mpnet_base_snli_mnli_en.md new file mode 100644 index 00000000000000..f19501355faf0f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-mpnet_base_snli_mnli_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mpnet_base_snli_mnli MPNetEmbeddings from symanto +author: John Snow Labs +name: mpnet_base_snli_mnli +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_snli_mnli` is a English model originally trained by symanto. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_snli_mnli_en_5.1.1_3.0_1694130311075.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_snli_mnli_en_5.1.1_3.0_1694130311075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("mpnet_base_snli_mnli","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("mpnet_base_snli_mnli", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_snli_mnli| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|404.3 MB| + +## References + +https://huggingface.co/symanto/mpnet-base-snli-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-mpnet_mnr_v2_fine_tuned_en.md b/docs/_posts/ahmedlone127/2023-09-07-mpnet_mnr_v2_fine_tuned_en.md new file mode 100644 index 00000000000000..ef6b64c7633596 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-mpnet_mnr_v2_fine_tuned_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mpnet_mnr_v2_fine_tuned MPNetEmbeddings from BlazingFringe +author: John Snow Labs +name: mpnet_mnr_v2_fine_tuned +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_mnr_v2_fine_tuned` is a English model originally trained by BlazingFringe. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_mnr_v2_fine_tuned_en_5.1.1_3.0_1694130647094.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_mnr_v2_fine_tuned_en_5.1.1_3.0_1694130647094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("mpnet_mnr_v2_fine_tuned","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("mpnet_mnr_v2_fine_tuned", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_mnr_v2_fine_tuned| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/BlazingFringe/mpnet-mnr-v2-fine-tuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-mpnet_multilabel_sector_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-mpnet_multilabel_sector_classifier_en.md new file mode 100644 index 00000000000000..24a4a489f1fb15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-mpnet_multilabel_sector_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mpnet_multilabel_sector_classifier MPNetEmbeddings from ppsingh +author: John Snow Labs +name: mpnet_multilabel_sector_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_multilabel_sector_classifier` is a English model originally trained by ppsingh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_multilabel_sector_classifier_en_5.1.1_3.0_1694131112892.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_multilabel_sector_classifier_en_5.1.1_3.0_1694131112892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("mpnet_multilabel_sector_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("mpnet_multilabel_sector_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_multilabel_sector_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/ppsingh/mpnet-multilabel-sector-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-mpnet_nli_sts_en.md b/docs/_posts/ahmedlone127/2023-09-07-mpnet_nli_sts_en.md new file mode 100644 index 00000000000000..9b20dfa2f6b007 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-mpnet_nli_sts_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mpnet_nli_sts MPNetEmbeddings from jamescalam +author: John Snow Labs +name: mpnet_nli_sts +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_nli_sts` is a English model originally trained by jamescalam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_nli_sts_en_5.1.1_3.0_1694123885821.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_nli_sts_en_5.1.1_3.0_1694123885821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("mpnet_nli_sts","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("mpnet_nli_sts", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_nli_sts| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|399.1 MB| + +## References + +https://huggingface.co/jamescalam/mpnet-nli-sts \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-mpnet_retriever_squad2_en.md b/docs/_posts/ahmedlone127/2023-09-07-mpnet_retriever_squad2_en.md new file mode 100644 index 00000000000000..1387032712dc14 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-mpnet_retriever_squad2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mpnet_retriever_squad2 MPNetEmbeddings from pinecone +author: John Snow Labs +name: mpnet_retriever_squad2 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_retriever_squad2` is a English model originally trained by pinecone. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_retriever_squad2_en_5.1.1_3.0_1694129132128.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_retriever_squad2_en_5.1.1_3.0_1694129132128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("mpnet_retriever_squad2","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("mpnet_retriever_squad2", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_retriever_squad2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/pinecone/mpnet-retriever-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-mpnet_snli_en.md b/docs/_posts/ahmedlone127/2023-09-07-mpnet_snli_en.md new file mode 100644 index 00000000000000..4eb8e51979a46a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-mpnet_snli_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mpnet_snli Mpnet from jamescalam +author: John Snow Labs +name: mpnet_snli +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_snli` is a English model originally trained by jamescalam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_snli_en_5.1.1_3.0_1694122601394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_snli_en_5.1.1_3.0_1694122601394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("mpnet_snli","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("mpnet_snli", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_snli| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|396.4 MB| + +## References + +https://huggingface.co/jamescalam/mpnet-snli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-mpnet_snli_negatives_en.md b/docs/_posts/ahmedlone127/2023-09-07-mpnet_snli_negatives_en.md new file mode 100644 index 00000000000000..19cf04d8846547 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-mpnet_snli_negatives_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mpnet_snli_negatives MPNetEmbeddings from jamescalam +author: John Snow Labs +name: mpnet_snli_negatives +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_snli_negatives` is a English model originally trained by jamescalam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_snli_negatives_en_5.1.1_3.0_1694123768227.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_snli_negatives_en_5.1.1_3.0_1694123768227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("mpnet_snli_negatives","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("mpnet_snli_negatives", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_snli_negatives| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|398.1 MB| + +## References + +https://huggingface.co/jamescalam/mpnet-snli-negatives \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_cos_v1_navteca_en.md b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_cos_v1_navteca_en.md new file mode 100644 index 00000000000000..1da37123a54d78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_cos_v1_navteca_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_mpnet_base_cos_v1_navteca MPNetEmbeddings from navteca +author: John Snow Labs +name: multi_qa_mpnet_base_cos_v1_navteca +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_cos_v1_navteca` is a English model originally trained by navteca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_cos_v1_navteca_en_5.1.1_3.0_1694124714786.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_cos_v1_navteca_en_5.1.1_3.0_1694124714786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_mpnet_base_cos_v1_navteca","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_mpnet_base_cos_v1_navteca", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_cos_v1_navteca| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/navteca/multi-qa-mpnet-base-cos-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_cos_v1_sentence_transformers_en.md b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_cos_v1_sentence_transformers_en.md new file mode 100644 index 00000000000000..c3387731a2ea8d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_cos_v1_sentence_transformers_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_mpnet_base_cos_v1_sentence_transformers MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: multi_qa_mpnet_base_cos_v1_sentence_transformers +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_cos_v1_sentence_transformers` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_cos_v1_sentence_transformers_en_5.1.1_3.0_1694129454272.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_cos_v1_sentence_transformers_en_5.1.1_3.0_1694129454272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_mpnet_base_cos_v1_sentence_transformers","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_mpnet_base_cos_v1_sentence_transformers", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_cos_v1_sentence_transformers| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/sentence-transformers/multi-qa-mpnet-base-cos-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_dot_v1_eclass_en.md b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_dot_v1_eclass_en.md new file mode 100644 index 00000000000000..6dbd652a4e48fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_dot_v1_eclass_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_mpnet_base_dot_v1_eclass MPNetEmbeddings from JoBeer +author: John Snow Labs +name: multi_qa_mpnet_base_dot_v1_eclass +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_dot_v1_eclass` is a English model originally trained by JoBeer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_eclass_en_5.1.1_3.0_1694127821437.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_eclass_en_5.1.1_3.0_1694127821437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_eclass","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_mpnet_base_dot_v1_eclass", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_dot_v1_eclass| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/JoBeer/multi-qa-mpnet-base-dot-v1-eclass \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_dot_v1_legal_finetune_en.md b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_dot_v1_legal_finetune_en.md new file mode 100644 index 00000000000000..f24c83762935d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_dot_v1_legal_finetune_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_mpnet_base_dot_v1_legal_finetune MPNetEmbeddings from oliviamga2 +author: John Snow Labs +name: multi_qa_mpnet_base_dot_v1_legal_finetune +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_dot_v1_legal_finetune` is a English model originally trained by oliviamga2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_legal_finetune_en_5.1.1_3.0_1694128585719.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_legal_finetune_en_5.1.1_3.0_1694128585719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_legal_finetune","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_mpnet_base_dot_v1_legal_finetune", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_dot_v1_legal_finetune| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/oliviamga2/multi-qa-mpnet-base-dot-v1_legal_finetune \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_dot_v1_sentence_transformers_en.md b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_dot_v1_sentence_transformers_en.md new file mode 100644 index 00000000000000..fd099032ab3896 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_mpnet_base_dot_v1_sentence_transformers_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_mpnet_base_dot_v1_sentence_transformers MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: multi_qa_mpnet_base_dot_v1_sentence_transformers +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_dot_v1_sentence_transformers` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_sentence_transformers_en_5.1.1_3.0_1694129579330.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_sentence_transformers_en_5.1.1_3.0_1694129579330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_sentence_transformers","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_mpnet_base_dot_v1_sentence_transformers", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_dot_v1_sentence_transformers| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/sentence-transformers/multi-qa-mpnet-base-dot-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-multi_qa_v1_mpnet_asymmetric_a_en.md b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_v1_mpnet_asymmetric_a_en.md new file mode 100644 index 00000000000000..1b700e5c8cca65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_v1_mpnet_asymmetric_a_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_v1_mpnet_asymmetric_a MPNetEmbeddings from flax-sentence-embeddings +author: John Snow Labs +name: multi_qa_v1_mpnet_asymmetric_a +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_v1_mpnet_asymmetric_a` is a English model originally trained by flax-sentence-embeddings. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_v1_mpnet_asymmetric_a_en_5.1.1_3.0_1694123866355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_v1_mpnet_asymmetric_a_en_5.1.1_3.0_1694123866355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_v1_mpnet_asymmetric_a","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_v1_mpnet_asymmetric_a", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_v1_mpnet_asymmetric_a| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/flax-sentence-embeddings/multi-QA_v1-mpnet-asymmetric-A \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-multi_qa_v1_mpnet_asymmetric_q_en.md b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_v1_mpnet_asymmetric_q_en.md new file mode 100644 index 00000000000000..c688cc63c1b0b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_v1_mpnet_asymmetric_q_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_v1_mpnet_asymmetric_q MPNetEmbeddings from flax-sentence-embeddings +author: John Snow Labs +name: multi_qa_v1_mpnet_asymmetric_q +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_v1_mpnet_asymmetric_q` is a English model originally trained by flax-sentence-embeddings. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_v1_mpnet_asymmetric_q_en_5.1.1_3.0_1694128463061.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_v1_mpnet_asymmetric_q_en_5.1.1_3.0_1694128463061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_v1_mpnet_asymmetric_q","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_v1_mpnet_asymmetric_q", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_v1_mpnet_asymmetric_q| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.4 MB| + +## References + +https://huggingface.co/flax-sentence-embeddings/multi-QA_v1-mpnet-asymmetric-Q \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-multi_qa_v1_mpnet_cls_dot_en.md b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_v1_mpnet_cls_dot_en.md new file mode 100644 index 00000000000000..649ad5625b79c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-multi_qa_v1_mpnet_cls_dot_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_v1_mpnet_cls_dot MPNetEmbeddings from flax-sentence-embeddings +author: John Snow Labs +name: multi_qa_v1_mpnet_cls_dot +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_v1_mpnet_cls_dot` is a English model originally trained by flax-sentence-embeddings. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_v1_mpnet_cls_dot_en_5.1.1_3.0_1694128566724.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_v1_mpnet_cls_dot_en_5.1.1_3.0_1694128566724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_v1_mpnet_cls_dot","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_v1_mpnet_cls_dot", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_v1_mpnet_cls_dot| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/flax-sentence-embeddings/multi-qa_v1-mpnet-cls_dot \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-negation_categories_classifier_es.md b/docs/_posts/ahmedlone127/2023-09-07-negation_categories_classifier_es.md new file mode 100644 index 00000000000000..e0a5fc50515b85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-negation_categories_classifier_es.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Castilian, Spanish negation_categories_classifier MPNetEmbeddings from mhammadkhan +author: John Snow Labs +name: negation_categories_classifier +date: 2023-09-07 +tags: [mpnet, es, open_source, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`negation_categories_classifier` is a Castilian, Spanish model originally trained by mhammadkhan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/negation_categories_classifier_es_5.1.1_3.0_1694130051743.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/negation_categories_classifier_es_5.1.1_3.0_1694130051743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("negation_categories_classifier","es") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("negation_categories_classifier", "es") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|negation_categories_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|es| +|Size:|406.9 MB| + +## References + +https://huggingface.co/mhammadkhan/negation-categories-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-nli_mpnet_base_v2_sentence_transformers_en.md b/docs/_posts/ahmedlone127/2023-09-07-nli_mpnet_base_v2_sentence_transformers_en.md new file mode 100644 index 00000000000000..1ba2f4dcb4932e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-nli_mpnet_base_v2_sentence_transformers_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English nli_mpnet_base_v2_sentence_transformers MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: nli_mpnet_base_v2_sentence_transformers +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nli_mpnet_base_v2_sentence_transformers` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nli_mpnet_base_v2_sentence_transformers_en_5.1.1_3.0_1694129705610.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nli_mpnet_base_v2_sentence_transformers_en_5.1.1_3.0_1694129705610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("nli_mpnet_base_v2_sentence_transformers","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("nli_mpnet_base_v2_sentence_transformers", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nli_mpnet_base_v2_sentence_transformers| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|405.5 MB| + +## References + +https://huggingface.co/sentence-transformers/nli-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-nooks_amd_detection_realtime_en.md b/docs/_posts/ahmedlone127/2023-09-07-nooks_amd_detection_realtime_en.md new file mode 100644 index 00000000000000..318e8315b4dcb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-nooks_amd_detection_realtime_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English nooks_amd_detection_realtime MPNetEmbeddings from nikcheerla +author: John Snow Labs +name: nooks_amd_detection_realtime +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nooks_amd_detection_realtime` is a English model originally trained by nikcheerla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nooks_amd_detection_realtime_en_5.1.1_3.0_1694123725819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nooks_amd_detection_realtime_en_5.1.1_3.0_1694123725819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("nooks_amd_detection_realtime","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("nooks_amd_detection_realtime", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nooks_amd_detection_realtime| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/nikcheerla/nooks-amd-detection-realtime \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-nooks_amd_detection_v2_full_en.md b/docs/_posts/ahmedlone127/2023-09-07-nooks_amd_detection_v2_full_en.md new file mode 100644 index 00000000000000..4a7b7157a599d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-nooks_amd_detection_v2_full_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English nooks_amd_detection_v2_full MPNetEmbeddings from nikcheerla +author: John Snow Labs +name: nooks_amd_detection_v2_full +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nooks_amd_detection_v2_full` is a English model originally trained by nikcheerla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nooks_amd_detection_v2_full_en_5.1.1_3.0_1694128051636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nooks_amd_detection_v2_full_en_5.1.1_3.0_1694128051636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("nooks_amd_detection_v2_full","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("nooks_amd_detection_v2_full", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nooks_amd_detection_v2_full| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/nikcheerla/nooks-amd-detection-v2-full \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-nps_psb_lds_en.md b/docs/_posts/ahmedlone127/2023-09-07-nps_psb_lds_en.md new file mode 100644 index 00000000000000..2e2e6e2593f597 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-nps_psb_lds_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English nps_psb_lds MPNetEmbeddings from nategro +author: John Snow Labs +name: nps_psb_lds +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nps_psb_lds` is a English model originally trained by nategro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nps_psb_lds_en_5.1.1_3.0_1694124378110.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nps_psb_lds_en_5.1.1_3.0_1694124378110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("nps_psb_lds","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("nps_psb_lds", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nps_psb_lds| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/nategro/nps-psb-lds \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-ouvrage_classif_en.md b/docs/_posts/ahmedlone127/2023-09-07-ouvrage_classif_en.md new file mode 100644 index 00000000000000..11b92018130918 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-ouvrage_classif_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English ouvrage_classif Mpnet from TomPWM +author: John Snow Labs +name: ouvrage_classif +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ouvrage_classif` is a English model originally trained by TomPWM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ouvrage_classif_en_5.1.1_3.0_1694122940260.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ouvrage_classif_en_5.1.1_3.0_1694122940260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("ouvrage_classif","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("ouvrage_classif", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ouvrage_classif| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/TomPWM/ouvrage-classif \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-paraphrase_mpnet_base_v2_fuzzy_matcher_en.md b/docs/_posts/ahmedlone127/2023-09-07-paraphrase_mpnet_base_v2_fuzzy_matcher_en.md new file mode 100644 index 00000000000000..af6220ebe31d6b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-paraphrase_mpnet_base_v2_fuzzy_matcher_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English paraphrase_mpnet_base_v2_fuzzy_matcher MPNetEmbeddings from shahrukhx01 +author: John Snow Labs +name: paraphrase_mpnet_base_v2_fuzzy_matcher +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_fuzzy_matcher` is a English model originally trained by shahrukhx01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_fuzzy_matcher_en_5.1.1_3.0_1694130070040.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_fuzzy_matcher_en_5.1.1_3.0_1694130070040.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_fuzzy_matcher","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("paraphrase_mpnet_base_v2_fuzzy_matcher", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|paraphrase_mpnet_base_v2_fuzzy_matcher| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/shahrukhx01/paraphrase-mpnet-base-v2-fuzzy-matcher \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-paraphrase_mpnet_base_v2_sentence_transformers_en.md b/docs/_posts/ahmedlone127/2023-09-07-paraphrase_mpnet_base_v2_sentence_transformers_en.md new file mode 100644 index 00000000000000..6e2070d571fd59 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-paraphrase_mpnet_base_v2_sentence_transformers_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English paraphrase_mpnet_base_v2_sentence_transformers MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: paraphrase_mpnet_base_v2_sentence_transformers +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_sentence_transformers` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_sentence_transformers_en_5.1.1_3.0_1694129822133.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_sentence_transformers_en_5.1.1_3.0_1694129822133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_sentence_transformers","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("paraphrase_mpnet_base_v2_sentence_transformers", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|paraphrase_mpnet_base_v2_sentence_transformers| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-paraphrase_mpnet_base_v2_setfit_sst2_en.md b/docs/_posts/ahmedlone127/2023-09-07-paraphrase_mpnet_base_v2_setfit_sst2_en.md new file mode 100644 index 00000000000000..176cb9767a0be6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-paraphrase_mpnet_base_v2_setfit_sst2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English paraphrase_mpnet_base_v2_setfit_sst2 MPNetEmbeddings from moshew +author: John Snow Labs +name: paraphrase_mpnet_base_v2_setfit_sst2 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_setfit_sst2` is a English model originally trained by moshew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_setfit_sst2_en_5.1.1_3.0_1694126561425.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_setfit_sst2_en_5.1.1_3.0_1694126561425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_setfit_sst2","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("paraphrase_mpnet_base_v2_setfit_sst2", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|paraphrase_mpnet_base_v2_setfit_sst2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/moshew/paraphrase-mpnet-base-v2_SetFit_sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-patentsberta_en.md b/docs/_posts/ahmedlone127/2023-09-07-patentsberta_en.md new file mode 100644 index 00000000000000..455d28a99079b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-patentsberta_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English patentsberta MPNetEmbeddings from AI-Growth-Lab +author: John Snow Labs +name: patentsberta +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`patentsberta` is a English model originally trained by AI-Growth-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/patentsberta_en_5.1.1_3.0_1694127839013.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/patentsberta_en_5.1.1_3.0_1694127839013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("patentsberta","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("patentsberta", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|patentsberta| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/AI-Growth-Lab/PatentSBERTa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-pdfsegs_en.md b/docs/_posts/ahmedlone127/2023-09-07-pdfsegs_en.md new file mode 100644 index 00000000000000..4ebc29044ebea6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-pdfsegs_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English pdfsegs MPNetEmbeddings from HamzaFarhan +author: John Snow Labs +name: pdfsegs +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pdfsegs` is a English model originally trained by HamzaFarhan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pdfsegs_en_5.1.1_3.0_1694126162854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pdfsegs_en_5.1.1_3.0_1694126162854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("pdfsegs","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("pdfsegs", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pdfsegs| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/HamzaFarhan/PDFSegs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-pharo_collaborators_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-pharo_collaborators_classifier_en.md new file mode 100644 index 00000000000000..b27c7a5cab5eef --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-pharo_collaborators_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English pharo_collaborators_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: pharo_collaborators_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pharo_collaborators_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pharo_collaborators_classifier_en_5.1.1_3.0_1694126370511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pharo_collaborators_classifier_en_5.1.1_3.0_1694126370511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("pharo_collaborators_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("pharo_collaborators_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pharo_collaborators_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AISE-TUDelft/pharo-collaborators-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-pharo_example_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-pharo_example_classifier_en.md new file mode 100644 index 00000000000000..3b27b5a4a948a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-pharo_example_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English pharo_example_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: pharo_example_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pharo_example_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pharo_example_classifier_en_5.1.1_3.0_1694130749424.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pharo_example_classifier_en_5.1.1_3.0_1694130749424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("pharo_example_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("pharo_example_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pharo_example_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AISE-TUDelft/pharo-example-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-pharo_keyimplementationpoints_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-pharo_keyimplementationpoints_classifier_en.md new file mode 100644 index 00000000000000..6538b55c49fc74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-pharo_keyimplementationpoints_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English pharo_keyimplementationpoints_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: pharo_keyimplementationpoints_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pharo_keyimplementationpoints_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pharo_keyimplementationpoints_classifier_en_5.1.1_3.0_1694129873019.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pharo_keyimplementationpoints_classifier_en_5.1.1_3.0_1694129873019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("pharo_keyimplementationpoints_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("pharo_keyimplementationpoints_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pharo_keyimplementationpoints_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AISE-TUDelft/pharo-keyimplementationpoints-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-pharo_responsibilities_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-pharo_responsibilities_classifier_en.md new file mode 100644 index 00000000000000..6772d835c6e16c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-pharo_responsibilities_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English pharo_responsibilities_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: pharo_responsibilities_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pharo_responsibilities_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pharo_responsibilities_classifier_en_5.1.1_3.0_1694130852738.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pharo_responsibilities_classifier_en_5.1.1_3.0_1694130852738.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("pharo_responsibilities_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("pharo_responsibilities_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pharo_responsibilities_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AISE-TUDelft/pharo-responsibilities-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-python_developmentnotes_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-python_developmentnotes_classifier_en.md new file mode 100644 index 00000000000000..7a363cb5ca7426 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-python_developmentnotes_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English python_developmentnotes_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: python_developmentnotes_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`python_developmentnotes_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/python_developmentnotes_classifier_en_5.1.1_3.0_1694129762240.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/python_developmentnotes_classifier_en_5.1.1_3.0_1694129762240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("python_developmentnotes_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("python_developmentnotes_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|python_developmentnotes_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AISE-TUDelft/python-developmentnotes-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-python_expand_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-python_expand_classifier_en.md new file mode 100644 index 00000000000000..8de227a5ff14f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-python_expand_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English python_expand_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: python_expand_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`python_expand_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/python_expand_classifier_en_5.1.1_3.0_1694126229745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/python_expand_classifier_en_5.1.1_3.0_1694126229745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("python_expand_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("python_expand_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|python_expand_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AISE-TUDelft/python-expand-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-python_parameters_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-python_parameters_classifier_en.md new file mode 100644 index 00000000000000..d18faf1ec21f89 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-python_parameters_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English python_parameters_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: python_parameters_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`python_parameters_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/python_parameters_classifier_en_5.1.1_3.0_1694130111574.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/python_parameters_classifier_en_5.1.1_3.0_1694130111574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("python_parameters_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("python_parameters_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|python_parameters_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AISE-TUDelft/python-parameters-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-python_summary_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-python_summary_classifier_en.md new file mode 100644 index 00000000000000..af155ba8188ff5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-python_summary_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English python_summary_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: python_summary_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`python_summary_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/python_summary_classifier_en_5.1.1_3.0_1694125555047.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/python_summary_classifier_en_5.1.1_3.0_1694125555047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("python_summary_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("python_summary_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|python_summary_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AISE-TUDelft/python-summary-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-python_usage_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-python_usage_classifier_en.md new file mode 100644 index 00000000000000..a018e34a5e3a4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-python_usage_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English python_usage_classifier MPNetEmbeddings from AISE-TUDelft +author: John Snow Labs +name: python_usage_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`python_usage_classifier` is a English model originally trained by AISE-TUDelft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/python_usage_classifier_en_5.1.1_3.0_1694130638732.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/python_usage_classifier_en_5.1.1_3.0_1694130638732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("python_usage_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("python_usage_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|python_usage_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AISE-TUDelft/python-usage-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-reddit_single_context_mpnet_base_en.md b/docs/_posts/ahmedlone127/2023-09-07-reddit_single_context_mpnet_base_en.md new file mode 100644 index 00000000000000..7e1bae83d6a63e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-reddit_single_context_mpnet_base_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English reddit_single_context_mpnet_base MPNetEmbeddings from flax-sentence-embeddings +author: John Snow Labs +name: reddit_single_context_mpnet_base +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reddit_single_context_mpnet_base` is a English model originally trained by flax-sentence-embeddings. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reddit_single_context_mpnet_base_en_5.1.1_3.0_1694124367563.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reddit_single_context_mpnet_base_en_5.1.1_3.0_1694124367563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("reddit_single_context_mpnet_base","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("reddit_single_context_mpnet_base", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reddit_single_context_mpnet_base| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/flax-sentence-embeddings/reddit_single-context_mpnet-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-retriever_coding_guru_adapted_en.md b/docs/_posts/ahmedlone127/2023-09-07-retriever_coding_guru_adapted_en.md new file mode 100644 index 00000000000000..5058151444fdc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-retriever_coding_guru_adapted_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English retriever_coding_guru_adapted MPNetEmbeddings from AlekseyKorshuk +author: John Snow Labs +name: retriever_coding_guru_adapted +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`retriever_coding_guru_adapted` is a English model originally trained by AlekseyKorshuk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/retriever_coding_guru_adapted_en_5.1.1_3.0_1694130068115.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/retriever_coding_guru_adapted_en_5.1.1_3.0_1694130068115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("retriever_coding_guru_adapted","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("retriever_coding_guru_adapted", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|retriever_coding_guru_adapted| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/AlekseyKorshuk/retriever-coding-guru-adapted \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-review_intent_20230116_en.md b/docs/_posts/ahmedlone127/2023-09-07-review_intent_20230116_en.md new file mode 100644 index 00000000000000..73a3657748b441 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-review_intent_20230116_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English review_intent_20230116 MPNetEmbeddings from meichen91 +author: John Snow Labs +name: review_intent_20230116 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`review_intent_20230116` is a English model originally trained by meichen91. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/review_intent_20230116_en_5.1.1_3.0_1694128378940.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/review_intent_20230116_en_5.1.1_3.0_1694128378940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("review_intent_20230116","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("review_intent_20230116", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|review_intent_20230116| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/meichen91/review_intent_20230116 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-review_multiclass_20230116_en.md b/docs/_posts/ahmedlone127/2023-09-07-review_multiclass_20230116_en.md new file mode 100644 index 00000000000000..c0e1f7dd34e5b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-review_multiclass_20230116_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English review_multiclass_20230116 MPNetEmbeddings from meichen91 +author: John Snow Labs +name: review_multiclass_20230116 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`review_multiclass_20230116` is a English model originally trained by meichen91. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/review_multiclass_20230116_en_5.1.1_3.0_1694128480525.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/review_multiclass_20230116_en_5.1.1_3.0_1694128480525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("review_multiclass_20230116","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("review_multiclass_20230116", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|review_multiclass_20230116| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/meichen91/review_multiclass_20230116 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-sb_temfac_en.md b/docs/_posts/ahmedlone127/2023-09-07-sb_temfac_en.md new file mode 100644 index 00000000000000..c7c119507b1403 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-sb_temfac_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English sb_temfac MPNetEmbeddings from stealthpy +author: John Snow Labs +name: sb_temfac +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sb_temfac` is a English model originally trained by stealthpy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sb_temfac_en_5.1.1_3.0_1694123355976.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sb_temfac_en_5.1.1_3.0_1694123355976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("sb_temfac","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("sb_temfac", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sb_temfac| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/stealthpy/sb-temfac \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-sbert_paper_en.md b/docs/_posts/ahmedlone127/2023-09-07-sbert_paper_en.md new file mode 100644 index 00000000000000..d71df9bc5fa15a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-sbert_paper_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English sbert_paper MPNetEmbeddings from salsabiilashifa11 +author: John Snow Labs +name: sbert_paper +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sbert_paper` is a English model originally trained by salsabiilashifa11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sbert_paper_en_5.1.1_3.0_1694125460196.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sbert_paper_en_5.1.1_3.0_1694125460196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("sbert_paper","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("sbert_paper", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sbert_paper| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/salsabiilashifa11/sbert-paper \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-sentence_transformers_bible_reference_final_en.md b/docs/_posts/ahmedlone127/2023-09-07-sentence_transformers_bible_reference_final_en.md new file mode 100644 index 00000000000000..16988365732d59 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-sentence_transformers_bible_reference_final_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English sentence_transformers_bible_reference_final MPNetEmbeddings from odunola +author: John Snow Labs +name: sentence_transformers_bible_reference_final +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_transformers_bible_reference_final` is a English model originally trained by odunola. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_bible_reference_final_en_5.1.1_3.0_1694128406180.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_bible_reference_final_en_5.1.1_3.0_1694128406180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("sentence_transformers_bible_reference_final","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("sentence_transformers_bible_reference_final", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentence_transformers_bible_reference_final| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/odunola/sentence-transformers-bible-reference-final \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-sentiment140_fewshot_en.md b/docs/_posts/ahmedlone127/2023-09-07-sentiment140_fewshot_en.md new file mode 100644 index 00000000000000..39b4e7a7a5f9b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-sentiment140_fewshot_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English sentiment140_fewshot MPNetEmbeddings from pig4431 +author: John Snow Labs +name: sentiment140_fewshot +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment140_fewshot` is a English model originally trained by pig4431. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment140_fewshot_en_5.1.1_3.0_1694130309466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment140_fewshot_en_5.1.1_3.0_1694130309466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("sentiment140_fewshot","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("sentiment140_fewshot", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment140_fewshot| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/pig4431/Sentiment140_fewshot \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_ag_news_endpoint_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_ag_news_endpoint_en.md new file mode 100644 index 00000000000000..3e1f79c843e2a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_ag_news_endpoint_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_ag_news_endpoint MPNetEmbeddings from philschmid +author: John Snow Labs +name: setfit_ag_news_endpoint +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_ag_news_endpoint` is a English model originally trained by philschmid. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_ag_news_endpoint_en_5.1.1_3.0_1694129573309.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_ag_news_endpoint_en_5.1.1_3.0_1694129573309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_ag_news_endpoint","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_ag_news_endpoint", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_ag_news_endpoint| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/philschmid/setfit-ag-news-endpoint \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_all_data_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_all_data_en.md new file mode 100644 index 00000000000000..98340da2e7ed0f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_all_data_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_all_data MPNetEmbeddings from scaperex +author: John Snow Labs +name: setfit_all_data +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_all_data` is a English model originally trained by scaperex. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_all_data_en_5.1.1_3.0_1694131075651.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_all_data_en_5.1.1_3.0_1694131075651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_all_data","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_all_data", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_all_data| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/scaperex/SetFit-all-data \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_alpaca_spanish_unprocessable_sample_detection_es.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_alpaca_spanish_unprocessable_sample_detection_es.md new file mode 100644 index 00000000000000..3a645313e1cdc0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_alpaca_spanish_unprocessable_sample_detection_es.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Castilian, Spanish setfit_alpaca_spanish_unprocessable_sample_detection MPNetEmbeddings from hackathon-somos-nlp-2023 +author: John Snow Labs +name: setfit_alpaca_spanish_unprocessable_sample_detection +date: 2023-09-07 +tags: [mpnet, es, open_source, onnx] +task: Embeddings +language: es +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_alpaca_spanish_unprocessable_sample_detection` is a Castilian, Spanish model originally trained by hackathon-somos-nlp-2023. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_alpaca_spanish_unprocessable_sample_detection_es_5.1.1_3.0_1694128554320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_alpaca_spanish_unprocessable_sample_detection_es_5.1.1_3.0_1694128554320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_alpaca_spanish_unprocessable_sample_detection","es") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_alpaca_spanish_unprocessable_sample_detection", "es") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_alpaca_spanish_unprocessable_sample_detection| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|es| +|Size:|407.2 MB| + +## References + +https://huggingface.co/hackathon-somos-nlp-2023/setfit-alpaca-es-unprocessable-sample-detection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_1_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_1_en.md new file mode 100644 index 00000000000000..7dc463687ca081 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_ds_version_0_0_1 MPNetEmbeddings from amittian +author: John Snow Labs +name: setfit_ds_version_0_0_1 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_ds_version_0_0_1` is a English model originally trained by amittian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_ds_version_0_0_1_en_5.1.1_3.0_1694124869162.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_ds_version_0_0_1_en_5.1.1_3.0_1694124869162.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_ds_version_0_0_1","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_ds_version_0_0_1", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_ds_version_0_0_1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/amittian/setfit_ds_version_0_0_1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_2_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_2_en.md new file mode 100644 index 00000000000000..867617435c338c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_ds_version_0_0_2 MPNetEmbeddings from amittian +author: John Snow Labs +name: setfit_ds_version_0_0_2 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_ds_version_0_0_2` is a English model originally trained by amittian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_ds_version_0_0_2_en_5.1.1_3.0_1694125015548.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_ds_version_0_0_2_en_5.1.1_3.0_1694125015548.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_ds_version_0_0_2","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_ds_version_0_0_2", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_ds_version_0_0_2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/amittian/setfit_ds_version_0_0_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_4_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_4_en.md new file mode 100644 index 00000000000000..098836f8e09639 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_4_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_ds_version_0_0_4 MPNetEmbeddings from amittian +author: John Snow Labs +name: setfit_ds_version_0_0_4 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_ds_version_0_0_4` is a English model originally trained by amittian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_ds_version_0_0_4_en_5.1.1_3.0_1694129561333.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_ds_version_0_0_4_en_5.1.1_3.0_1694129561333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_ds_version_0_0_4","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_ds_version_0_0_4", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_ds_version_0_0_4| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/amittian/setfit_ds_version_0_0_4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_5_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_5_en.md new file mode 100644 index 00000000000000..a6c6aa4de8a2f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_ds_version_0_0_5_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_ds_version_0_0_5 MPNetEmbeddings from amittian +author: John Snow Labs +name: setfit_ds_version_0_0_5 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_ds_version_0_0_5` is a English model originally trained by amittian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_ds_version_0_0_5_en_5.1.1_3.0_1694125459042.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_ds_version_0_0_5_en_5.1.1_3.0_1694125459042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_ds_version_0_0_5","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_ds_version_0_0_5", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_ds_version_0_0_5| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/amittian/setfit_ds_version_0_0_5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_ethos_multilabel_example_lewtun_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_ethos_multilabel_example_lewtun_en.md new file mode 100644 index 00000000000000..9b0ca6cdd2a9e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_ethos_multilabel_example_lewtun_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_ethos_multilabel_example_lewtun MPNetEmbeddings from lewtun +author: John Snow Labs +name: setfit_ethos_multilabel_example_lewtun +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_ethos_multilabel_example_lewtun` is a English model originally trained by lewtun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_ethos_multilabel_example_lewtun_en_5.1.1_3.0_1694130189052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_ethos_multilabel_example_lewtun_en_5.1.1_3.0_1694130189052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_ethos_multilabel_example_lewtun","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_ethos_multilabel_example_lewtun", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_ethos_multilabel_example_lewtun| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/lewtun/setfit-ethos-multilabel-example \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_ethos_multilabel_example_neilthematic_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_ethos_multilabel_example_neilthematic_en.md new file mode 100644 index 00000000000000..972f464a1395ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_ethos_multilabel_example_neilthematic_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_ethos_multilabel_example_neilthematic MPNetEmbeddings from neilthematic +author: John Snow Labs +name: setfit_ethos_multilabel_example_neilthematic +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_ethos_multilabel_example_neilthematic` is a English model originally trained by neilthematic. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_ethos_multilabel_example_neilthematic_en_5.1.1_3.0_1694128696798.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_ethos_multilabel_example_neilthematic_en_5.1.1_3.0_1694128696798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_ethos_multilabel_example_neilthematic","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_ethos_multilabel_example_neilthematic", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_ethos_multilabel_example_neilthematic| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/neilthematic/setfit-ethos-multilabel-example \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_few_shot_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_few_shot_classifier_en.md new file mode 100644 index 00000000000000..9a5a9a80274ebe --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_few_shot_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_few_shot_classifier MPNetEmbeddings from Kuaaangwen +author: John Snow Labs +name: setfit_few_shot_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_few_shot_classifier` is a English model originally trained by Kuaaangwen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_few_shot_classifier_en_5.1.1_3.0_1694127951811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_few_shot_classifier_en_5.1.1_3.0_1694127951811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_few_shot_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_few_shot_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_few_shot_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/Kuaaangwen/Setfit-few-shot-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_finetuned_financial_text_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_finetuned_financial_text_en.md new file mode 100644 index 00000000000000..41345e1d5b25ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_finetuned_financial_text_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_finetuned_financial_text MPNetEmbeddings from nickmuchi +author: John Snow Labs +name: setfit_finetuned_financial_text +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_finetuned_financial_text` is a English model originally trained by nickmuchi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_finetuned_financial_text_en_5.1.1_3.0_1694124680784.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_finetuned_financial_text_en_5.1.1_3.0_1694124680784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_finetuned_financial_text","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_finetuned_financial_text", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_finetuned_financial_text| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/nickmuchi/setfit-finetuned-financial-text \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_model_pradipta11_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_model_pradipta11_en.md new file mode 100644 index 00000000000000..7451bd425acb40 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_model_pradipta11_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_model_pradipta11 MPNetEmbeddings from Pradipta11 +author: John Snow Labs +name: setfit_model_pradipta11 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_pradipta11` is a English model originally trained by Pradipta11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_pradipta11_en_5.1.1_3.0_1694128986439.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_pradipta11_en_5.1.1_3.0_1694128986439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_model_pradipta11","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_model_pradipta11", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_model_pradipta11| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Pradipta11/setfit-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_model_rajistics_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_model_rajistics_en.md new file mode 100644 index 00000000000000..f8976c2df06c62 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_model_rajistics_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_model_rajistics MPNetEmbeddings from rajistics +author: John Snow Labs +name: setfit_model_rajistics +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_rajistics` is a English model originally trained by rajistics. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_rajistics_en_5.1.1_3.0_1694129815092.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_rajistics_en_5.1.1_3.0_1694129815092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_model_rajistics","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_model_rajistics", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_model_rajistics| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/rajistics/setfit-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_model_test_sensitve_v1_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_model_test_sensitve_v1_en.md new file mode 100644 index 00000000000000..1b6e5b948163a0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_model_test_sensitve_v1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_model_test_sensitve_v1 MPNetEmbeddings from Adipta +author: John Snow Labs +name: setfit_model_test_sensitve_v1 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_test_sensitve_v1` is a English model originally trained by Adipta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_test_sensitve_v1_en_5.1.1_3.0_1694125258840.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_test_sensitve_v1_en_5.1.1_3.0_1694125258840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_model_test_sensitve_v1","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_model_test_sensitve_v1", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_model_test_sensitve_v1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Adipta/setfit-model-test-sensitve-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_occupation_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_occupation_en.md new file mode 100644 index 00000000000000..6a0849f0a25aa6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_occupation_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_occupation MPNetEmbeddings from ivanzidov +author: John Snow Labs +name: setfit_occupation +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_occupation` is a English model originally trained by ivanzidov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_occupation_en_5.1.1_3.0_1694125793111.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_occupation_en_5.1.1_3.0_1694125793111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_occupation","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_occupation", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_occupation| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/ivanzidov/setfit-occupation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_comm_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_comm_en.md new file mode 100644 index 00000000000000..91c4e14679722c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_comm_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p1_comm MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p1_comm +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p1_comm` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p1_comm_en_5.1.1_3.0_1694128840558.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p1_comm_en_5.1.1_3.0_1694128840558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p1_comm","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p1_comm", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p1_comm| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p1-comm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_en.md new file mode 100644 index 00000000000000..1ac2188323fcb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p1 MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p1 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p1` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p1_en_5.1.1_3.0_1694131074420.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p1_en_5.1.1_3.0_1694131074420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p1","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p1", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_life_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_life_en.md new file mode 100644 index 00000000000000..ac7b31d35b2925 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_life_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p1_life MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p1_life +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p1_life` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p1_life_en_5.1.1_3.0_1694128968448.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p1_life_en_5.1.1_3.0_1694128968448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p1_life","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p1_life", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p1_life| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p1-life \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_likes_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_likes_en.md new file mode 100644 index 00000000000000..cc2308a516eaf2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p1_likes_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p1_likes MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p1_likes +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p1_likes` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p1_likes_en_5.1.1_3.0_1694130957746.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p1_likes_en_5.1.1_3.0_1694130957746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p1_likes","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p1_likes", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p1_likes| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p1-likes \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p3_func_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p3_func_en.md new file mode 100644 index 00000000000000..c25173bb2c9229 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p3_func_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p3_func MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p3_func +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p3_func` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_func_en_5.1.1_3.0_1694128269303.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_func_en_5.1.1_3.0_1694128269303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p3_func","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p3_func", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p3_func| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p3-func \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p3_sev_en.md b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p3_sev_en.md new file mode 100644 index 00000000000000..2470877b9dadce --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-setfit_zero_shot_classification_pbsp_p3_sev_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p3_sev MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p3_sev +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p3_sev` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_sev_en_5.1.1_3.0_1694126027402.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_sev_en_5.1.1_3.0_1694126027402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p3_sev","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p3_sev", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p3_sev| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p3-sev \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-shona_mpnet_base_snli_mnli_en.md b/docs/_posts/ahmedlone127/2023-09-07-shona_mpnet_base_snli_mnli_en.md new file mode 100644 index 00000000000000..da00824661f0c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-shona_mpnet_base_snli_mnli_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English shona_mpnet_base_snli_mnli MPNetEmbeddings from symanto +author: John Snow Labs +name: shona_mpnet_base_snli_mnli +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`shona_mpnet_base_snli_mnli` is a English model originally trained by symanto. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/shona_mpnet_base_snli_mnli_en_5.1.1_3.0_1694126372344.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/shona_mpnet_base_snli_mnli_en_5.1.1_3.0_1694126372344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("shona_mpnet_base_snli_mnli","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("shona_mpnet_base_snli_mnli", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|shona_mpnet_base_snli_mnli| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/symanto/sn-mpnet-base-snli-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-sml_ukr_message_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-07-sml_ukr_message_classifier_en.md new file mode 100644 index 00000000000000..a046db097809b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-sml_ukr_message_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English sml_ukr_message_classifier MPNetEmbeddings from rodekruis +author: John Snow Labs +name: sml_ukr_message_classifier +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sml_ukr_message_classifier` is a English model originally trained by rodekruis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sml_ukr_message_classifier_en_5.1.1_3.0_1694127978542.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sml_ukr_message_classifier_en_5.1.1_3.0_1694127978542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("sml_ukr_message_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("sml_ukr_message_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sml_ukr_message_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/rodekruis/sml-ukr-message-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-sml_ukr_word_classifier_medium_en.md b/docs/_posts/ahmedlone127/2023-09-07-sml_ukr_word_classifier_medium_en.md new file mode 100644 index 00000000000000..a4cbc69a46720d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-sml_ukr_word_classifier_medium_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English sml_ukr_word_classifier_medium MPNetEmbeddings from rodekruis +author: John Snow Labs +name: sml_ukr_word_classifier_medium +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sml_ukr_word_classifier_medium` is a English model originally trained by rodekruis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sml_ukr_word_classifier_medium_en_5.1.1_3.0_1694129410581.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sml_ukr_word_classifier_medium_en_5.1.1_3.0_1694129410581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("sml_ukr_word_classifier_medium","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("sml_ukr_word_classifier_medium", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sml_ukr_word_classifier_medium| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/rodekruis/sml-ukr-word-classifier-medium \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-spiced_en.md b/docs/_posts/ahmedlone127/2023-09-07-spiced_en.md new file mode 100644 index 00000000000000..bd1ef7411b483b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-spiced_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English spiced MPNetEmbeddings from copenlu +author: John Snow Labs +name: spiced +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spiced` is a English model originally trained by copenlu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spiced_en_5.1.1_3.0_1694128411873.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spiced_en_5.1.1_3.0_1694128411873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("spiced","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("spiced", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spiced| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/copenlu/spiced \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-stackoverflow_mpnet_base_en.md b/docs/_posts/ahmedlone127/2023-09-07-stackoverflow_mpnet_base_en.md new file mode 100644 index 00000000000000..3f40800faed42e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-stackoverflow_mpnet_base_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English stackoverflow_mpnet_base MPNetEmbeddings from flax-sentence-embeddings +author: John Snow Labs +name: stackoverflow_mpnet_base +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stackoverflow_mpnet_base` is a English model originally trained by flax-sentence-embeddings. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stackoverflow_mpnet_base_en_5.1.1_3.0_1694128832593.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stackoverflow_mpnet_base_en_5.1.1_3.0_1694128832593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("stackoverflow_mpnet_base","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("stackoverflow_mpnet_base", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|stackoverflow_mpnet_base| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/flax-sentence-embeddings/stackoverflow_mpnet-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-stsb_mpnet_base_v2_en.md b/docs/_posts/ahmedlone127/2023-09-07-stsb_mpnet_base_v2_en.md new file mode 100644 index 00000000000000..90b776d91f0e98 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-stsb_mpnet_base_v2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English stsb_mpnet_base_v2 MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: stsb_mpnet_base_v2 +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stsb_mpnet_base_v2` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stsb_mpnet_base_v2_en_5.1.1_3.0_1694129940879.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stsb_mpnet_base_v2_en_5.1.1_3.0_1694129940879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("stsb_mpnet_base_v2","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("stsb_mpnet_base_v2", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|stsb_mpnet_base_v2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|405.6 MB| + +## References + +https://huggingface.co/sentence-transformers/stsb-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-test_food_en.md b/docs/_posts/ahmedlone127/2023-09-07-test_food_en.md new file mode 100644 index 00000000000000..9cca95eb6ebdb8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-test_food_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English test_food MPNetEmbeddings from Linus4Lyf +author: John Snow Labs +name: test_food +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_food` is a English model originally trained by Linus4Lyf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_food_en_5.1.1_3.0_1694125513298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_food_en_5.1.1_3.0_1694125513298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("test_food","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("test_food", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_food| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/Linus4Lyf/test-food \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-testing_setfit_en.md b/docs/_posts/ahmedlone127/2023-09-07-testing_setfit_en.md new file mode 100644 index 00000000000000..0ea4d6c55ed45d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-testing_setfit_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English testing_setfit MPNetEmbeddings from BernierS +author: John Snow Labs +name: testing_setfit +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testing_setfit` is a English model originally trained by BernierS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testing_setfit_en_5.1.1_3.0_1694128182708.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testing_setfit_en_5.1.1_3.0_1694128182708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("testing_setfit","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("testing_setfit", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|testing_setfit| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/BernierS/Testing_Setfit \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnet_hf_internal_testing_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnet_hf_internal_testing_en.md new file mode 100644 index 00000000000000..b9d6f3fccd1e5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnet_hf_internal_testing_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnet_hf_internal_testing MPNetEmbeddings from hf-internal-testing +author: John Snow Labs +name: tiny_random_mpnet_hf_internal_testing +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnet_hf_internal_testing` is a English model originally trained by hf-internal-testing. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnet_hf_internal_testing_en_5.1.1_3.0_1694128912406.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnet_hf_internal_testing_en_5.1.1_3.0_1694128912406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnet_hf_internal_testing","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnet_hf_internal_testing", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnet_hf_internal_testing| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.8 KB| + +## References + +https://huggingface.co/hf-internal-testing/tiny-random-mpnet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetformaskedlm_hf_internal_testing_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetformaskedlm_hf_internal_testing_en.md new file mode 100644 index 00000000000000..95a87e95432a50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetformaskedlm_hf_internal_testing_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetformaskedlm_hf_internal_testing MPNetEmbeddings from hf-internal-testing +author: John Snow Labs +name: tiny_random_mpnetformaskedlm_hf_internal_testing +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetformaskedlm_hf_internal_testing` is a English model originally trained by hf-internal-testing. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetformaskedlm_hf_internal_testing_en_5.1.1_3.0_1694126709962.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetformaskedlm_hf_internal_testing_en_5.1.1_3.0_1694126709962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetformaskedlm_hf_internal_testing","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetformaskedlm_hf_internal_testing", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetformaskedlm_hf_internal_testing| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.9 KB| + +## References + +https://huggingface.co/hf-internal-testing/tiny-random-MPNetForMaskedLM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetformaskedlm_hf_tiny_model_private_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetformaskedlm_hf_tiny_model_private_en.md new file mode 100644 index 00000000000000..7e370458b977a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetformaskedlm_hf_tiny_model_private_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetformaskedlm_hf_tiny_model_private MPNetEmbeddings from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_mpnetformaskedlm_hf_tiny_model_private +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetformaskedlm_hf_tiny_model_private` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetformaskedlm_hf_tiny_model_private_en_5.1.1_3.0_1694128151940.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetformaskedlm_hf_tiny_model_private_en_5.1.1_3.0_1694128151940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetformaskedlm_hf_tiny_model_private","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetformaskedlm_hf_tiny_model_private", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetformaskedlm_hf_tiny_model_private| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.8 KB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-MPNetForMaskedLM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetformultiplechoice_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetformultiplechoice_en.md new file mode 100644 index 00000000000000..057672f0ad2754 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetformultiplechoice_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetformultiplechoice MPNetEmbeddings from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_mpnetformultiplechoice +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetformultiplechoice` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetformultiplechoice_en_5.1.1_3.0_1694123775173.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetformultiplechoice_en_5.1.1_3.0_1694123775173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetformultiplechoice","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetformultiplechoice", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetformultiplechoice| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.7 KB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-MPNetForMultipleChoice \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforquestionanswering_hf_internal_testing_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforquestionanswering_hf_internal_testing_en.md new file mode 100644 index 00000000000000..1df34bf13fcbc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforquestionanswering_hf_internal_testing_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetforquestionanswering_hf_internal_testing MPNetEmbeddings from hf-internal-testing +author: John Snow Labs +name: tiny_random_mpnetforquestionanswering_hf_internal_testing +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetforquestionanswering_hf_internal_testing` is a English model originally trained by hf-internal-testing. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetforquestionanswering_hf_internal_testing_en_5.1.1_3.0_1694130790158.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetforquestionanswering_hf_internal_testing_en_5.1.1_3.0_1694130790158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetforquestionanswering_hf_internal_testing","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetforquestionanswering_hf_internal_testing", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetforquestionanswering_hf_internal_testing| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|878.0 KB| + +## References + +https://huggingface.co/hf-internal-testing/tiny-random-MPNetForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforquestionanswering_hf_tiny_model_private_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforquestionanswering_hf_tiny_model_private_en.md new file mode 100644 index 00000000000000..f9370bd7db0516 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforquestionanswering_hf_tiny_model_private_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetforquestionanswering_hf_tiny_model_private MPNetEmbeddings from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_mpnetforquestionanswering_hf_tiny_model_private +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetforquestionanswering_hf_tiny_model_private` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetforquestionanswering_hf_tiny_model_private_en_5.1.1_3.0_1694123843375.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetforquestionanswering_hf_tiny_model_private_en_5.1.1_3.0_1694123843375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetforquestionanswering_hf_tiny_model_private","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetforquestionanswering_hf_tiny_model_private", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetforquestionanswering_hf_tiny_model_private| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.9 KB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-MPNetForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforsequenceclassification_hf_internal_testing_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforsequenceclassification_hf_internal_testing_en.md new file mode 100644 index 00000000000000..417282d3428415 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforsequenceclassification_hf_internal_testing_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetforsequenceclassification_hf_internal_testing MPNetEmbeddings from hf-internal-testing +author: John Snow Labs +name: tiny_random_mpnetforsequenceclassification_hf_internal_testing +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetforsequenceclassification_hf_internal_testing` is a English model originally trained by hf-internal-testing. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetforsequenceclassification_hf_internal_testing_en_5.1.1_3.0_1694126839890.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetforsequenceclassification_hf_internal_testing_en_5.1.1_3.0_1694126839890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetforsequenceclassification_hf_internal_testing","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetforsequenceclassification_hf_internal_testing", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetforsequenceclassification_hf_internal_testing| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.9 KB| + +## References + +https://huggingface.co/hf-internal-testing/tiny-random-MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforsequenceclassification_hf_tiny_model_private_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforsequenceclassification_hf_tiny_model_private_en.md new file mode 100644 index 00000000000000..eb260ac309709f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetforsequenceclassification_hf_tiny_model_private_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetforsequenceclassification_hf_tiny_model_private MPNetEmbeddings from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_mpnetforsequenceclassification_hf_tiny_model_private +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetforsequenceclassification_hf_tiny_model_private` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetforsequenceclassification_hf_tiny_model_private_en_5.1.1_3.0_1694123901079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetforsequenceclassification_hf_tiny_model_private_en_5.1.1_3.0_1694123901079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetforsequenceclassification_hf_tiny_model_private","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetforsequenceclassification_hf_tiny_model_private", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetforsequenceclassification_hf_tiny_model_private| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.8 KB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetfortokenclassification_hf_internal_testing_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetfortokenclassification_hf_internal_testing_en.md new file mode 100644 index 00000000000000..d5e59377b06df4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetfortokenclassification_hf_internal_testing_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetfortokenclassification_hf_internal_testing MPNetEmbeddings from hf-internal-testing +author: John Snow Labs +name: tiny_random_mpnetfortokenclassification_hf_internal_testing +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetfortokenclassification_hf_internal_testing` is a English model originally trained by hf-internal-testing. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetfortokenclassification_hf_internal_testing_en_5.1.1_3.0_1694126904935.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetfortokenclassification_hf_internal_testing_en_5.1.1_3.0_1694126904935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetfortokenclassification_hf_internal_testing","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetfortokenclassification_hf_internal_testing", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetfortokenclassification_hf_internal_testing| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.8 KB| + +## References + +https://huggingface.co/hf-internal-testing/tiny-random-MPNetForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetfortokenclassification_hf_tiny_model_private_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetfortokenclassification_hf_tiny_model_private_en.md new file mode 100644 index 00000000000000..c1e208bf8aad21 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetfortokenclassification_hf_tiny_model_private_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetfortokenclassification_hf_tiny_model_private MPNetEmbeddings from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_mpnetfortokenclassification_hf_tiny_model_private +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetfortokenclassification_hf_tiny_model_private` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetfortokenclassification_hf_tiny_model_private_en_5.1.1_3.0_1694128395671.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetfortokenclassification_hf_tiny_model_private_en_5.1.1_3.0_1694128395671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetfortokenclassification_hf_tiny_model_private","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetfortokenclassification_hf_tiny_model_private", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetfortokenclassification_hf_tiny_model_private| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.6 KB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-MPNetForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetmodel_hf_internal_testing_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetmodel_hf_internal_testing_en.md new file mode 100644 index 00000000000000..864f8d80ab634d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetmodel_hf_internal_testing_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetmodel_hf_internal_testing MPNetEmbeddings from hf-internal-testing +author: John Snow Labs +name: tiny_random_mpnetmodel_hf_internal_testing +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetmodel_hf_internal_testing` is a English model originally trained by hf-internal-testing. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetmodel_hf_internal_testing_en_5.1.1_3.0_1694130963864.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetmodel_hf_internal_testing_en_5.1.1_3.0_1694130963864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetmodel_hf_internal_testing","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetmodel_hf_internal_testing", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetmodel_hf_internal_testing| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.9 KB| + +## References + +https://huggingface.co/hf-internal-testing/tiny-random-MPNetModel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetmodel_hf_tiny_model_private_en.md b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetmodel_hf_tiny_model_private_en.md new file mode 100644 index 00000000000000..3b380efd311580 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-tiny_random_mpnetmodel_hf_tiny_model_private_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_random_mpnetmodel_hf_tiny_model_private MPNetEmbeddings from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_mpnetmodel_hf_tiny_model_private +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_mpnetmodel_hf_tiny_model_private` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetmodel_hf_tiny_model_private_en_5.1.1_3.0_1694128454499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_mpnetmodel_hf_tiny_model_private_en_5.1.1_3.0_1694128454499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("tiny_random_mpnetmodel_hf_tiny_model_private","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("tiny_random_mpnetmodel_hf_tiny_model_private", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_mpnetmodel_hf_tiny_model_private| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|877.9 KB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-MPNetModel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-07-vulnerable_groups_en.md b/docs/_posts/ahmedlone127/2023-09-07-vulnerable_groups_en.md new file mode 100644 index 00000000000000..744d9aecfdb19d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-07-vulnerable_groups_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English vulnerable_groups MPNetEmbeddings from leavoigt +author: John Snow Labs +name: vulnerable_groups +date: 2023-09-07 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vulnerable_groups` is a English model originally trained by leavoigt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vulnerable_groups_en_5.1.1_3.0_1694129396114.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vulnerable_groups_en_5.1.1_3.0_1694129396114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("vulnerable_groups","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("vulnerable_groups", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vulnerable_groups| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/leavoigt/vulnerable_groups \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_questions_clustering_english_en.md b/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_questions_clustering_english_en.md new file mode 100644 index 00000000000000..eb2099e78d45c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_questions_clustering_english_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_questions_clustering_english MPNetEmbeddings from aiknowyou +author: John Snow Labs +name: all_mpnet_base_questions_clustering_english +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_questions_clustering_english` is a English model originally trained by aiknowyou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_questions_clustering_english_en_5.1.1_3.0_1694131732803.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_questions_clustering_english_en_5.1.1_3.0_1694131732803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_questions_clustering_english","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_questions_clustering_english", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_questions_clustering_english| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aiknowyou/all-mpnet-base-questions-clustering-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_v2_en.md b/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_v2_en.md new file mode 100644 index 00000000000000..a2bd2a65b27eee --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_v2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2 MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: all_mpnet_base_v2 +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_en_5.1.1_3.0_1694164524893.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_en_5.1.1_3.0_1694164524893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/sentence-transformers/all-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_v2_feature_extraction_en.md b/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_v2_feature_extraction_en.md new file mode 100644 index 00000000000000..d8ad11d0837f8a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_v2_feature_extraction_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_feature_extraction MPNetEmbeddings from guidecare +author: John Snow Labs +name: all_mpnet_base_v2_feature_extraction +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_feature_extraction` is a English model originally trained by guidecare. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_feature_extraction_en_5.1.1_3.0_1694131495572.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_feature_extraction_en_5.1.1_3.0_1694131495572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_feature_extraction","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_feature_extraction", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_feature_extraction| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.6 MB| + +## References + +https://huggingface.co/guidecare/all-mpnet-base-v2-feature-extraction \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_v2_for_sb_clustering_en.md b/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_v2_for_sb_clustering_en.md new file mode 100644 index 00000000000000..9679a527d2d9ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-all_mpnet_base_v2_for_sb_clustering_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English all_mpnet_base_v2_for_sb_clustering MPNetEmbeddings from Thabet +author: John Snow Labs +name: all_mpnet_base_v2_for_sb_clustering +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_for_sb_clustering` is a English model originally trained by Thabet. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_for_sb_clustering_en_5.1.1_3.0_1694131254349.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_for_sb_clustering_en_5.1.1_3.0_1694131254349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("all_mpnet_base_v2_for_sb_clustering","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("all_mpnet_base_v2_for_sb_clustering", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_for_sb_clustering| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/Thabet/all-mpnet-base-v2_for_sb_clustering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-cpu_target_classifier_en.md b/docs/_posts/ahmedlone127/2023-09-08-cpu_target_classifier_en.md new file mode 100644 index 00000000000000..2abbe2611066a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-cpu_target_classifier_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English cpu_target_classifier MPNetEmbeddings from mtyrrell +author: John Snow Labs +name: cpu_target_classifier +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cpu_target_classifier` is a English model originally trained by mtyrrell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cpu_target_classifier_en_5.1.1_3.0_1694131643680.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cpu_target_classifier_en_5.1.1_3.0_1694131643680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("cpu_target_classifier","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("cpu_target_classifier", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cpu_target_classifier| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/mtyrrell/CPU_Target_Classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-esci_jp_mpnet_crossencoder_en.md b/docs/_posts/ahmedlone127/2023-09-08-esci_jp_mpnet_crossencoder_en.md new file mode 100644 index 00000000000000..63f1a9f6c8fd53 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-esci_jp_mpnet_crossencoder_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English esci_jp_mpnet_crossencoder MPNetEmbeddings from spacemanidol +author: John Snow Labs +name: esci_jp_mpnet_crossencoder +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esci_jp_mpnet_crossencoder` is a English model originally trained by spacemanidol. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esci_jp_mpnet_crossencoder_en_5.1.1_3.0_1694131619285.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esci_jp_mpnet_crossencoder_en_5.1.1_3.0_1694131619285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("esci_jp_mpnet_crossencoder","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("esci_jp_mpnet_crossencoder", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esci_jp_mpnet_crossencoder| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/spacemanidol/esci-jp-mpnet-crossencoder \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-eth_setfit_payment_model_en.md b/docs/_posts/ahmedlone127/2023-09-08-eth_setfit_payment_model_en.md new file mode 100644 index 00000000000000..c58d76b782fdea --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-eth_setfit_payment_model_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English eth_setfit_payment_model MPNetEmbeddings from kainxwang +author: John Snow Labs +name: eth_setfit_payment_model +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eth_setfit_payment_model` is a English model originally trained by kainxwang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eth_setfit_payment_model_en_5.1.1_3.0_1694131517678.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eth_setfit_payment_model_en_5.1.1_3.0_1694131517678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("eth_setfit_payment_model","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("eth_setfit_payment_model", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|eth_setfit_payment_model| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/kainxwang/eth-setfit-payment-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-few_shot_model_en.md b/docs/_posts/ahmedlone127/2023-09-08-few_shot_model_en.md new file mode 100644 index 00000000000000..5226f69d8f13a4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-few_shot_model_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English few_shot_model MPNetEmbeddings from jessietextstan +author: John Snow Labs +name: few_shot_model +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`few_shot_model` is a English model originally trained by jessietextstan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/few_shot_model_en_5.1.1_3.0_1694131785073.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/few_shot_model_en_5.1.1_3.0_1694131785073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("few_shot_model","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("few_shot_model", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|few_shot_model| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/jessietextstan/few-shot-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-multi_qa_mpnet_base_cos_v1_en.md b/docs/_posts/ahmedlone127/2023-09-08-multi_qa_mpnet_base_cos_v1_en.md new file mode 100644 index 00000000000000..78ca405367341c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-multi_qa_mpnet_base_cos_v1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_mpnet_base_cos_v1 MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: multi_qa_mpnet_base_cos_v1 +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_cos_v1` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_cos_v1_en_5.1.1_3.0_1694164524065.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_cos_v1_en_5.1.1_3.0_1694164524065.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_mpnet_base_cos_v1","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_mpnet_base_cos_v1", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_cos_v1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/sentence-transformers/multi-qa-mpnet-base-cos-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-multi_qa_mpnet_base_dot_v1_en.md b/docs/_posts/ahmedlone127/2023-09-08-multi_qa_mpnet_base_dot_v1_en.md new file mode 100644 index 00000000000000..131d76f36c24a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-multi_qa_mpnet_base_dot_v1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_mpnet_base_dot_v1 MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: multi_qa_mpnet_base_dot_v1 +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_dot_v1` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_en_5.1.1_3.0_1694164614713.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_en_5.1.1_3.0_1694164614713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_mpnet_base_dot_v1", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_dot_v1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/sentence-transformers/multi-qa-mpnet-base-dot-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-multi_qa_mpnet_base_dot_v1_model_embeddings_en.md b/docs/_posts/ahmedlone127/2023-09-08-multi_qa_mpnet_base_dot_v1_model_embeddings_en.md new file mode 100644 index 00000000000000..b608ef602d7bb4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-multi_qa_mpnet_base_dot_v1_model_embeddings_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English multi_qa_mpnet_base_dot_v1_model_embeddings MPNetEmbeddings from model-embeddings +author: John Snow Labs +name: multi_qa_mpnet_base_dot_v1_model_embeddings +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_dot_v1_model_embeddings` is a English model originally trained by model-embeddings. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_model_embeddings_en_5.1.1_3.0_1694131503800.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_model_embeddings_en_5.1.1_3.0_1694131503800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_model_embeddings","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("multi_qa_mpnet_base_dot_v1_model_embeddings", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi_qa_mpnet_base_dot_v1_model_embeddings| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/model-embeddings/multi-qa-mpnet-base-dot-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-nli_mpnet_base_v2_en.md b/docs/_posts/ahmedlone127/2023-09-08-nli_mpnet_base_v2_en.md new file mode 100644 index 00000000000000..d74b0a6c585501 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-nli_mpnet_base_v2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English nli_mpnet_base_v2 MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: nli_mpnet_base_v2 +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nli_mpnet_base_v2` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nli_mpnet_base_v2_en_5.1.1_3.0_1694164513118.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nli_mpnet_base_v2_en_5.1.1_3.0_1694164513118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("nli_mpnet_base_v2","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("nli_mpnet_base_v2", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nli_mpnet_base_v2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|405.5 MB| + +## References + +https://huggingface.co/sentence-transformers/nli-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-paraphrase_mpnet_base_v2_en.md b/docs/_posts/ahmedlone127/2023-09-08-paraphrase_mpnet_base_v2_en.md new file mode 100644 index 00000000000000..781d343be18885 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-paraphrase_mpnet_base_v2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English paraphrase_mpnet_base_v2 MPNetEmbeddings from sentence-transformers +author: John Snow Labs +name: paraphrase_mpnet_base_v2 +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2` is a English model originally trained by sentence-transformers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_en_5.1.1_3.0_1694164524556.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_en_5.1.1_3.0_1694164524556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("paraphrase_mpnet_base_v2", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|paraphrase_mpnet_base_v2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-paraphrase_mpnet_base_v2_finetuned_polifact_en.md b/docs/_posts/ahmedlone127/2023-09-08-paraphrase_mpnet_base_v2_finetuned_polifact_en.md new file mode 100644 index 00000000000000..e1f1a5b83d23e7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-paraphrase_mpnet_base_v2_finetuned_polifact_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English paraphrase_mpnet_base_v2_finetuned_polifact MPNetEmbeddings from anuj55 +author: John Snow Labs +name: paraphrase_mpnet_base_v2_finetuned_polifact +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_finetuned_polifact` is a English model originally trained by anuj55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_finetuned_polifact_en_5.1.1_3.0_1694131210870.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_finetuned_polifact_en_5.1.1_3.0_1694131210870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_finetuned_polifact","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("paraphrase_mpnet_base_v2_finetuned_polifact", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|paraphrase_mpnet_base_v2_finetuned_polifact| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/anuj55/paraphrase-mpnet-base-v2-finetuned-polifact \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-patentsberta_v2_en.md b/docs/_posts/ahmedlone127/2023-09-08-patentsberta_v2_en.md new file mode 100644 index 00000000000000..d8b4738e4bc070 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-patentsberta_v2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English patentsberta_v2 MPNetEmbeddings from AAUBS +author: John Snow Labs +name: patentsberta_v2 +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`patentsberta_v2` is a English model originally trained by AAUBS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/patentsberta_v2_en_5.1.1_3.0_1694131353971.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/patentsberta_v2_en_5.1.1_3.0_1694131353971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("patentsberta_v2","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("patentsberta_v2", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|patentsberta_v2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.4 MB| + +## References + +https://huggingface.co/AAUBS/PatentSBERTa_V2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_ft_sentinent_eval_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_ft_sentinent_eval_en.md new file mode 100644 index 00000000000000..45f673fb2a38d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_ft_sentinent_eval_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_ft_sentinent_eval MPNetEmbeddings from StatsGary +author: John Snow Labs +name: setfit_ft_sentinent_eval +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_ft_sentinent_eval` is a English model originally trained by StatsGary. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_ft_sentinent_eval_en_5.1.1_3.0_1694132009719.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_ft_sentinent_eval_en_5.1.1_3.0_1694132009719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_ft_sentinent_eval","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_ft_sentinent_eval", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_ft_sentinent_eval| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/StatsGary/setfit-ft-sentinent-eval \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_model_feb11_misinformation_on_law_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_model_feb11_misinformation_on_law_en.md new file mode 100644 index 00000000000000..3c585db18a2196 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_model_feb11_misinformation_on_law_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_model_feb11_misinformation_on_law MPNetEmbeddings from mitra-mir +author: John Snow Labs +name: setfit_model_feb11_misinformation_on_law +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_feb11_misinformation_on_law` is a English model originally trained by mitra-mir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_feb11_misinformation_on_law_en_5.1.1_3.0_1694131910541.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_feb11_misinformation_on_law_en_5.1.1_3.0_1694131910541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_model_feb11_misinformation_on_law","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_model_feb11_misinformation_on_law", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_model_feb11_misinformation_on_law| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/mitra-mir/setfit-model-Feb11-Misinformation-on-Law \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_ostrom_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_ostrom_en.md new file mode 100644 index 00000000000000..92bee868df0b21 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_ostrom_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_ostrom MPNetEmbeddings from mahaswec +author: John Snow Labs +name: setfit_ostrom +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_ostrom` is a English model originally trained by mahaswec. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_ostrom_en_5.1.1_3.0_1694131365430.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_ostrom_en_5.1.1_3.0_1694131365430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_ostrom","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_ostrom", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_ostrom| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/mahaswec/setfit_ostrom \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_bhvr_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_bhvr_en.md new file mode 100644 index 00000000000000..eb7e529bd36574 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_bhvr_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p3_bhvr MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p3_bhvr +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p3_bhvr` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_bhvr_en_5.1.1_3.0_1694131223110.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_bhvr_en_5.1.1_3.0_1694131223110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p3_bhvr","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p3_bhvr", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p3_bhvr| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p3-bhvr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_cons_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_cons_en.md new file mode 100644 index 00000000000000..efdd4f8cb14c2b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_cons_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p3_cons MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p3_cons +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p3_cons` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_cons_en_5.1.1_3.0_1694131904273.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_cons_en_5.1.1_3.0_1694131904273.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p3_cons","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p3_cons", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p3_cons| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p3-cons \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_dur_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_dur_en.md new file mode 100644 index 00000000000000..0699084d7a40a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_dur_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p3_dur MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p3_dur +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p3_dur` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_dur_en_5.1.1_3.0_1694131370642.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_dur_en_5.1.1_3.0_1694131370642.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p3_dur","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p3_dur", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p3_dur| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p3-dur \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_trig_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_trig_en.md new file mode 100644 index 00000000000000..e622b812b9e93e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p3_trig_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p3_trig MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p3_trig +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p3_trig` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_trig_en_5.1.1_3.0_1694131664015.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_trig_en_5.1.1_3.0_1694131664015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p3_trig","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p3_trig", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p3_trig| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p3-trig \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_achiev_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_achiev_en.md new file mode 100644 index 00000000000000..37b13d9bc75bfa --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_achiev_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p4_achiev MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p4_achiev +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p4_achiev` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p4_achiev_en_5.1.1_3.0_1694131523151.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p4_achiev_en_5.1.1_3.0_1694131523151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p4_achiev","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p4_achiev", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p4_achiev| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p4-achiev \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_meas_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_meas_en.md new file mode 100644 index 00000000000000..f6588e4fbef863 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_meas_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p4_meas MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p4_meas +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p4_meas` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p4_meas_en_5.1.1_3.0_1694131375079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p4_meas_en_5.1.1_3.0_1694131375079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p4_meas","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p4_meas", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p4_meas| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p4-meas \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_rel_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_rel_en.md new file mode 100644 index 00000000000000..3e49849a78cc9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_rel_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p4_rel MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p4_rel +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p4_rel` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p4_rel_en_5.1.1_3.0_1694131656638.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p4_rel_en_5.1.1_3.0_1694131656638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p4_rel","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p4_rel", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p4_rel| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p4-rel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_specific_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_specific_en.md new file mode 100644 index 00000000000000..742c48339a1a50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_specific_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p4_specific MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p4_specific +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p4_specific` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p4_specific_en_5.1.1_3.0_1694131229509.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p4_specific_en_5.1.1_3.0_1694131229509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p4_specific","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p4_specific", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p4_specific| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p4-specific \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_time_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_time_en.md new file mode 100644 index 00000000000000..9a87f506d20bb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_p4_time_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_p4_time MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_p4_time +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p4_time` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p4_time_en_5.1.1_3.0_1694131780751.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p4_time_en_5.1.1_3.0_1694131780751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_p4_time","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_p4_time", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_p4_time| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p4-time \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_q8a_azure_gpt35_en.md b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_q8a_azure_gpt35_en.md new file mode 100644 index 00000000000000..c57d017d9bae16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-setfit_zero_shot_classification_pbsp_q8a_azure_gpt35_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English setfit_zero_shot_classification_pbsp_q8a_azure_gpt35 MPNetEmbeddings from aammari +author: John Snow Labs +name: setfit_zero_shot_classification_pbsp_q8a_azure_gpt35 +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_q8a_azure_gpt35` is a English model originally trained by aammari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_q8a_azure_gpt35_en_5.1.1_3.0_1694131776102.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_q8a_azure_gpt35_en_5.1.1_3.0_1694131776102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("setfit_zero_shot_classification_pbsp_q8a_azure_gpt35","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("setfit_zero_shot_classification_pbsp_q8a_azure_gpt35", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_zero_shot_classification_pbsp_q8a_azure_gpt35| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-q8a-azure-gpt35 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-08-test_model_001_en.md b/docs/_posts/ahmedlone127/2023-09-08-test_model_001_en.md new file mode 100644 index 00000000000000..0ab02d9cce413d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-08-test_model_001_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English test_model_001 MPNetEmbeddings from intellya22 +author: John Snow Labs +name: test_model_001 +date: 2023-09-08 +tags: [mpnet, en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_001` is a English model originally trained by intellya22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_001_en_5.1.1_3.0_1694131205719.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_001_en_5.1.1_3.0_1694131205719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =MPNetEmbeddings.pretrained("test_model_001","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("mpnet_embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("documents") + +val embeddings = MPNetEmbeddings + .pretrained("test_model_001", "en") + .setInputCols(Array("documents")) + .setOutputCol("mpnet_embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_model_001| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[mpnet_embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/intellya22/test-model-001 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-222_en.md b/docs/_posts/ahmedlone127/2023-09-09-222_en.md new file mode 100644 index 00000000000000..d4f1b357ee8cd8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-222_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English 222 BertEmbeddings from junzai +author: John Snow Labs +name: 222 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`222` is a English model originally trained by junzai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/222_en_5.1.1_3.0_1694284019307.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/222_en_5.1.1_3.0_1694284019307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("222","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("222", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|222| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/junzai/222 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-absa_maskedlm_en.md b/docs/_posts/ahmedlone127/2023-09-09-absa_maskedlm_en.md new file mode 100644 index 00000000000000..6e0ed5b0a845b5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-absa_maskedlm_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English absa_maskedlm BertEmbeddings from UchihaMadara +author: John Snow Labs +name: absa_maskedlm +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`absa_maskedlm` is a English model originally trained by UchihaMadara. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/absa_maskedlm_en_5.1.1_3.0_1694284442111.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/absa_maskedlm_en_5.1.1_3.0_1694284442111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("absa_maskedlm","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("absa_maskedlm", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|absa_maskedlm| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/UchihaMadara/ABSA-MaskedLM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-adaptive_lm_molecules_en.md b/docs/_posts/ahmedlone127/2023-09-09-adaptive_lm_molecules_en.md new file mode 100644 index 00000000000000..c84859d17d32aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-adaptive_lm_molecules_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English adaptive_lm_molecules BertEmbeddings from mossaic-candle +author: John Snow Labs +name: adaptive_lm_molecules +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adaptive_lm_molecules` is a English model originally trained by mossaic-candle. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adaptive_lm_molecules_en_5.1.1_3.0_1694282672899.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adaptive_lm_molecules_en_5.1.1_3.0_1694282672899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("adaptive_lm_molecules","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("adaptive_lm_molecules", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|adaptive_lm_molecules| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|263.8 MB| + +## References + +https://huggingface.co/mossaic-candle/adaptive-lm-molecules \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-aethiqs_base_bertje_data_rotterdam_epochs_10_en.md b/docs/_posts/ahmedlone127/2023-09-09-aethiqs_base_bertje_data_rotterdam_epochs_10_en.md new file mode 100644 index 00000000000000..43d43d688ae696 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-aethiqs_base_bertje_data_rotterdam_epochs_10_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English aethiqs_base_bertje_data_rotterdam_epochs_10 BertEmbeddings from AethiQs-Max +author: John Snow Labs +name: aethiqs_base_bertje_data_rotterdam_epochs_10 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aethiqs_base_bertje_data_rotterdam_epochs_10` is a English model originally trained by AethiQs-Max. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aethiqs_base_bertje_data_rotterdam_epochs_10_en_5.1.1_3.0_1694260296232.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aethiqs_base_bertje_data_rotterdam_epochs_10_en_5.1.1_3.0_1694260296232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("aethiqs_base_bertje_data_rotterdam_epochs_10","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("aethiqs_base_bertje_data_rotterdam_epochs_10", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aethiqs_base_bertje_data_rotterdam_epochs_10| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AethiQs-Max/aethiqs-base_bertje-data_rotterdam-epochs_10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30_en.md b/docs/_posts/ahmedlone127/2023-09-09-aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30_en.md new file mode 100644 index 00000000000000..a049d5aa5f4ac4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30 BertEmbeddings from AethiQs-Max +author: John Snow Labs +name: aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30` is a English model originally trained by AethiQs-Max. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30_en_5.1.1_3.0_1694260436558.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30_en_5.1.1_3.0_1694260436558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aethiqs_base_bertje_data_rotterdam_epochs_30_epoch_30| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AethiQs-Max/aethiqs-base_bertje-data_rotterdam-epochs_30-epoch_30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-aethiqs_gembert_bertje_50k_en.md b/docs/_posts/ahmedlone127/2023-09-09-aethiqs_gembert_bertje_50k_en.md new file mode 100644 index 00000000000000..c5922cf52a9aed --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-aethiqs_gembert_bertje_50k_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English aethiqs_gembert_bertje_50k BertEmbeddings from AethiQs-Max +author: John Snow Labs +name: aethiqs_gembert_bertje_50k +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aethiqs_gembert_bertje_50k` is a English model originally trained by AethiQs-Max. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aethiqs_gembert_bertje_50k_en_5.1.1_3.0_1694260128112.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aethiqs_gembert_bertje_50k_en_5.1.1_3.0_1694260128112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("aethiqs_gembert_bertje_50k","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("aethiqs_gembert_bertje_50k", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aethiqs_gembert_bertje_50k| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AethiQs-Max/AethiQs_GemBERT_bertje_50k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-ai12_junzai_en.md b/docs/_posts/ahmedlone127/2023-09-09-ai12_junzai_en.md new file mode 100644 index 00000000000000..92ffb5f30604b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-ai12_junzai_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English ai12_junzai BertEmbeddings from junzai +author: John Snow Labs +name: ai12_junzai +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai12_junzai` is a English model originally trained by junzai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai12_junzai_en_5.1.1_3.0_1694284179005.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai12_junzai_en_5.1.1_3.0_1694284179005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("ai12_junzai","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("ai12_junzai", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ai12_junzai| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/junzai/ai12 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-alephbertgimmel_10_epochs_en.md b/docs/_posts/ahmedlone127/2023-09-09-alephbertgimmel_10_epochs_en.md new file mode 100644 index 00000000000000..8bd444bfae6fe7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-alephbertgimmel_10_epochs_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English alephbertgimmel_10_epochs BertEmbeddings from Embible +author: John Snow Labs +name: alephbertgimmel_10_epochs +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alephbertgimmel_10_epochs` is a English model originally trained by Embible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alephbertgimmel_10_epochs_en_5.1.1_3.0_1694259605594.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alephbertgimmel_10_epochs_en_5.1.1_3.0_1694259605594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("alephbertgimmel_10_epochs","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("alephbertgimmel_10_epochs", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|alephbertgimmel_10_epochs| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|690.3 MB| + +## References + +https://huggingface.co/Embible/AlephBertGimmel-10-epochs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-alephbertgimmel_20_epochs_en.md b/docs/_posts/ahmedlone127/2023-09-09-alephbertgimmel_20_epochs_en.md new file mode 100644 index 00000000000000..6254d9ff0fcaa7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-alephbertgimmel_20_epochs_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English alephbertgimmel_20_epochs BertEmbeddings from Embible +author: John Snow Labs +name: alephbertgimmel_20_epochs +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alephbertgimmel_20_epochs` is a English model originally trained by Embible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alephbertgimmel_20_epochs_en_5.1.1_3.0_1694259790377.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alephbertgimmel_20_epochs_en_5.1.1_3.0_1694259790377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("alephbertgimmel_20_epochs","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("alephbertgimmel_20_epochs", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|alephbertgimmel_20_epochs| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|690.3 MB| + +## References + +https://huggingface.co/Embible/AlephBertGimmel-20-epochs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-alephbertgimmel_50_epochs_en.md b/docs/_posts/ahmedlone127/2023-09-09-alephbertgimmel_50_epochs_en.md new file mode 100644 index 00000000000000..3816e91148def1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-alephbertgimmel_50_epochs_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English alephbertgimmel_50_epochs BertEmbeddings from Embible +author: John Snow Labs +name: alephbertgimmel_50_epochs +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alephbertgimmel_50_epochs` is a English model originally trained by Embible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alephbertgimmel_50_epochs_en_5.1.1_3.0_1694259959436.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alephbertgimmel_50_epochs_en_5.1.1_3.0_1694259959436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("alephbertgimmel_50_epochs","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("alephbertgimmel_50_epochs", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|alephbertgimmel_50_epochs| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|690.0 MB| + +## References + +https://huggingface.co/Embible/AlephBertGimmel-50-epochs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-alglegal3_bert_base_arabertv2_en.md b/docs/_posts/ahmedlone127/2023-09-09-alglegal3_bert_base_arabertv2_en.md new file mode 100644 index 00000000000000..908a790f6a0698 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-alglegal3_bert_base_arabertv2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English alglegal3_bert_base_arabertv2 BertEmbeddings from hatemestinbejaia +author: John Snow Labs +name: alglegal3_bert_base_arabertv2 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alglegal3_bert_base_arabertv2` is a English model originally trained by hatemestinbejaia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alglegal3_bert_base_arabertv2_en_5.1.1_3.0_1694279972460.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alglegal3_bert_base_arabertv2_en_5.1.1_3.0_1694279972460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("alglegal3_bert_base_arabertv2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("alglegal3_bert_base_arabertv2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|alglegal3_bert_base_arabertv2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|504.8 MB| + +## References + +https://huggingface.co/hatemestinbejaia/AlgLegal3_bert-base-arabertv2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-arabert32_flickr8k_en.md b/docs/_posts/ahmedlone127/2023-09-09-arabert32_flickr8k_en.md new file mode 100644 index 00000000000000..7d86d5ef95dee0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-arabert32_flickr8k_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English arabert32_flickr8k BertEmbeddings from jontooy +author: John Snow Labs +name: arabert32_flickr8k +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabert32_flickr8k` is a English model originally trained by jontooy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabert32_flickr8k_en_5.1.1_3.0_1694283279124.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabert32_flickr8k_en_5.1.1_3.0_1694283279124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("arabert32_flickr8k","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("arabert32_flickr8k", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabert32_flickr8k| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|505.1 MB| + +## References + +https://huggingface.co/jontooy/AraBERT32-Flickr8k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-arabic_mbertmodel_mberttok_en.md b/docs/_posts/ahmedlone127/2023-09-09-arabic_mbertmodel_mberttok_en.md new file mode 100644 index 00000000000000..e904b67348a0ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-arabic_mbertmodel_mberttok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English arabic_mbertmodel_mberttok BertEmbeddings from hgiyt +author: John Snow Labs +name: arabic_mbertmodel_mberttok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_mbertmodel_mberttok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabic_mbertmodel_mberttok_en_5.1.1_3.0_1694258818763.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_mbertmodel_mberttok_en_5.1.1_3.0_1694258818763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("arabic_mbertmodel_mberttok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("arabic_mbertmodel_mberttok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabic_mbertmodel_mberttok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|545.9 MB| + +## References + +https://huggingface.co/hgiyt/ar-mbertmodel-mberttok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-arabic_mbertmodel_monotok_adapter_en.md b/docs/_posts/ahmedlone127/2023-09-09-arabic_mbertmodel_monotok_adapter_en.md new file mode 100644 index 00000000000000..e71d7559eee9b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-arabic_mbertmodel_monotok_adapter_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English arabic_mbertmodel_monotok_adapter BertEmbeddings from hgiyt +author: John Snow Labs +name: arabic_mbertmodel_monotok_adapter +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_mbertmodel_monotok_adapter` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabic_mbertmodel_monotok_adapter_en_5.1.1_3.0_1694258970126.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_mbertmodel_monotok_adapter_en_5.1.1_3.0_1694258970126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("arabic_mbertmodel_monotok_adapter","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("arabic_mbertmodel_monotok_adapter", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabic_mbertmodel_monotok_adapter| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|505.0 MB| + +## References + +https://huggingface.co/hgiyt/ar-mbertmodel-monotok-adapter \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-arabic_mbertmodel_monotok_en.md b/docs/_posts/ahmedlone127/2023-09-09-arabic_mbertmodel_monotok_en.md new file mode 100644 index 00000000000000..0005089a4a791e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-arabic_mbertmodel_monotok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English arabic_mbertmodel_monotok BertEmbeddings from hgiyt +author: John Snow Labs +name: arabic_mbertmodel_monotok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_mbertmodel_monotok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabic_mbertmodel_monotok_en_5.1.1_3.0_1694259124754.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_mbertmodel_monotok_en_5.1.1_3.0_1694259124754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("arabic_mbertmodel_monotok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("arabic_mbertmodel_monotok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabic_mbertmodel_monotok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|505.0 MB| + +## References + +https://huggingface.co/hgiyt/ar-mbertmodel-monotok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-arabic_monomodel_mberttok_en.md b/docs/_posts/ahmedlone127/2023-09-09-arabic_monomodel_mberttok_en.md new file mode 100644 index 00000000000000..720a49cab11338 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-arabic_monomodel_mberttok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English arabic_monomodel_mberttok BertEmbeddings from hgiyt +author: John Snow Labs +name: arabic_monomodel_mberttok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_monomodel_mberttok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabic_monomodel_mberttok_en_5.1.1_3.0_1694259279000.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_monomodel_mberttok_en_5.1.1_3.0_1694259279000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("arabic_monomodel_mberttok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("arabic_monomodel_mberttok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabic_monomodel_mberttok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|545.3 MB| + +## References + +https://huggingface.co/hgiyt/ar-monomodel-mberttok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-arabic_monomodel_monotok_en.md b/docs/_posts/ahmedlone127/2023-09-09-arabic_monomodel_monotok_en.md new file mode 100644 index 00000000000000..775ea9ba366e70 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-arabic_monomodel_monotok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English arabic_monomodel_monotok BertEmbeddings from hgiyt +author: John Snow Labs +name: arabic_monomodel_monotok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_monomodel_monotok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabic_monomodel_monotok_en_5.1.1_3.0_1694259428031.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_monomodel_monotok_en_5.1.1_3.0_1694259428031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("arabic_monomodel_monotok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("arabic_monomodel_monotok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabic_monomodel_monotok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|504.1 MB| + +## References + +https://huggingface.co/hgiyt/ar-monomodel-monotok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bantu_bert_xx.md b/docs/_posts/ahmedlone127/2023-09-09-bantu_bert_xx.md new file mode 100644 index 00000000000000..b9f2468616edc5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bantu_bert_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual bantu_bert BertEmbeddings from nairaxo +author: John Snow Labs +name: bantu_bert +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bantu_bert` is a Multilingual model originally trained by nairaxo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bantu_bert_xx_5.1.1_3.0_1694282661097.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bantu_bert_xx_5.1.1_3.0_1694282661097.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bantu_bert","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bantu_bert", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bantu_bert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|752.8 MB| + +## References + +https://huggingface.co/nairaxo/bantu-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-base_mlm_imdb_en.md b/docs/_posts/ahmedlone127/2023-09-09-base_mlm_imdb_en.md new file mode 100644 index 00000000000000..ad797eaa2a29b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-base_mlm_imdb_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English base_mlm_imdb BertEmbeddings from muhtasham +author: John Snow Labs +name: base_mlm_imdb +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_mlm_imdb` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_mlm_imdb_en_5.1.1_3.0_1694258742410.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_mlm_imdb_en_5.1.1_3.0_1694258742410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("base_mlm_imdb","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("base_mlm_imdb", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|base_mlm_imdb| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.6 MB| + +## References + +https://huggingface.co/muhtasham/base-mlm-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert__racism80000_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert__racism80000_en.md new file mode 100644 index 00000000000000..844281cb6dbbf8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert__racism80000_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert__racism80000 BertEmbeddings from MutazYoune +author: John Snow Labs +name: bert__racism80000 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert__racism80000` is a English model originally trained by MutazYoune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert__racism80000_en_5.1.1_3.0_1694278959145.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert__racism80000_en_5.1.1_3.0_1694278959145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert__racism80000","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert__racism80000", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert__racism80000| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.4 MB| + +## References + +https://huggingface.co/MutazYoune/bert__racism80000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_aeslc_aktsvigun_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_aeslc_aktsvigun_en.md new file mode 100644 index 00000000000000..f0010b84d0cdf3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_aeslc_aktsvigun_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_aeslc_aktsvigun BertEmbeddings from Aktsvigun +author: John Snow Labs +name: bert_base_aeslc_aktsvigun +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_aeslc_aktsvigun` is a English model originally trained by Aktsvigun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_aeslc_aktsvigun_en_5.1.1_3.0_1694284037320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_aeslc_aktsvigun_en_5.1.1_3.0_1694284037320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_aeslc_aktsvigun","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_aeslc_aktsvigun", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_aeslc_aktsvigun| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/Aktsvigun/bert-base-aeslc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_aeslc_danish_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_aeslc_danish_en.md new file mode 100644 index 00000000000000..b96a08caf9ebc6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_aeslc_danish_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_aeslc_danish BertEmbeddings from kenkaneki +author: John Snow Labs +name: bert_base_aeslc_danish +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_aeslc_danish` is a English model originally trained by kenkaneki. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_aeslc_danish_en_5.1.1_3.0_1694283902070.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_aeslc_danish_en_5.1.1_3.0_1694283902070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_aeslc_danish","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_aeslc_danish", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_aeslc_danish| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/kenkaneki/bert-base-aeslc-da \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_aeslc_kenkaneki_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_aeslc_kenkaneki_en.md new file mode 100644 index 00000000000000..b00570b73050e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_aeslc_kenkaneki_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_aeslc_kenkaneki BertEmbeddings from kenkaneki +author: John Snow Labs +name: bert_base_aeslc_kenkaneki +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_aeslc_kenkaneki` is a English model originally trained by kenkaneki. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_aeslc_kenkaneki_en_5.1.1_3.0_1694284188438.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_aeslc_kenkaneki_en_5.1.1_3.0_1694284188438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_aeslc_kenkaneki","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_aeslc_kenkaneki", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_aeslc_kenkaneki| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/kenkaneki/bert-base-aeslc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabertv2_algarlegalbert_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabertv2_algarlegalbert_en.md new file mode 100644 index 00000000000000..f942e4c9350d25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabertv2_algarlegalbert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_arabertv2_algarlegalbert BertEmbeddings from hatemestinbejaia +author: John Snow Labs +name: bert_base_arabertv2_algarlegalbert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv2_algarlegalbert` is a English model originally trained by hatemestinbejaia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_algarlegalbert_en_5.1.1_3.0_1694279683923.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_algarlegalbert_en_5.1.1_3.0_1694279683923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_arabertv2_algarlegalbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_arabertv2_algarlegalbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabertv2_algarlegalbert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|504.8 MB| + +## References + +https://huggingface.co/hatemestinbejaia/bert-base-arabertv2-AlgArLegalBert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_catalan_ar.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_catalan_ar.md new file mode 100644 index 00000000000000..b536cd3a994515 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_catalan_ar.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Arabic bert_base_arabic_camelbert_catalan BertEmbeddings from CAMeL-Lab +author: John Snow Labs +name: bert_base_arabic_camelbert_catalan +date: 2023-09-09 +tags: [bert, ar, open_source, fill_mask, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_catalan` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_catalan_ar_5.1.1_3.0_1694265014880.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_catalan_ar_5.1.1_3.0_1694265014880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_arabic_camelbert_catalan","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_arabic_camelbert_catalan", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_catalan| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|406.6 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_danish_ar.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_danish_ar.md new file mode 100644 index 00000000000000..f95314aaeb3a18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_danish_ar.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Arabic bert_base_arabic_camelbert_danish BertEmbeddings from CAMeL-Lab +author: John Snow Labs +name: bert_base_arabic_camelbert_danish +date: 2023-09-09 +tags: [bert, ar, open_source, fill_mask, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_danish` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_danish_ar_5.1.1_3.0_1694265139823.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_danish_ar_5.1.1_3.0_1694265139823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_arabic_camelbert_danish","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_arabic_camelbert_danish", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_danish| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|406.7 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_mix_ar.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_mix_ar.md new file mode 100644 index 00000000000000..00e71eb80f25bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_mix_ar.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Arabic bert_base_arabic_camelbert_mix BertEmbeddings from CAMeL-Lab +author: John Snow Labs +name: bert_base_arabic_camelbert_mix +date: 2023-09-09 +tags: [bert, ar, open_source, fill_mask, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_mix` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_mix_ar_5.1.1_3.0_1694265271288.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_mix_ar_5.1.1_3.0_1694265271288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_arabic_camelbert_mix","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_arabic_camelbert_mix", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_mix| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|406.6 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_ar.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_ar.md new file mode 100644 index 00000000000000..255e8350f28897 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_ar.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Arabic bert_base_arabic_camelbert_msa BertEmbeddings from CAMeL-Lab +author: John Snow Labs +name: bert_base_arabic_camelbert_msa +date: 2023-09-09 +tags: [bert, ar, open_source, fill_mask, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_msa` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_ar_5.1.1_3.0_1694265945366.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_ar_5.1.1_3.0_1694265945366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_arabic_camelbert_msa","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_arabic_camelbert_msa", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_msa| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|406.3 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_eighth_ar.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_eighth_ar.md new file mode 100644 index 00000000000000..8dab1d62b4b18d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_eighth_ar.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Arabic bert_base_arabic_camelbert_msa_eighth BertEmbeddings from CAMeL-Lab +author: John Snow Labs +name: bert_base_arabic_camelbert_msa_eighth +date: 2023-09-09 +tags: [bert, ar, open_source, fill_mask, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_msa_eighth` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_eighth_ar_5.1.1_3.0_1694265412738.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_eighth_ar_5.1.1_3.0_1694265412738.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_arabic_camelbert_msa_eighth","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_arabic_camelbert_msa_eighth", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_msa_eighth| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|406.4 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_half_ar.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_half_ar.md new file mode 100644 index 00000000000000..43d39e82eed204 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_half_ar.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Arabic bert_base_arabic_camelbert_msa_half BertEmbeddings from CAMeL-Lab +author: John Snow Labs +name: bert_base_arabic_camelbert_msa_half +date: 2023-09-09 +tags: [bert, ar, open_source, fill_mask, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_msa_half` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_half_ar_5.1.1_3.0_1694265547981.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_half_ar_5.1.1_3.0_1694265547981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_arabic_camelbert_msa_half","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_arabic_camelbert_msa_half", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_msa_half| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|406.4 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-half \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_quarter_ar.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_quarter_ar.md new file mode 100644 index 00000000000000..c041ec5e73b569 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_quarter_ar.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Arabic bert_base_arabic_camelbert_msa_quarter BertEmbeddings from CAMeL-Lab +author: John Snow Labs +name: bert_base_arabic_camelbert_msa_quarter +date: 2023-09-09 +tags: [bert, ar, open_source, fill_mask, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_msa_quarter` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_quarter_ar_5.1.1_3.0_1694265681109.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_quarter_ar_5.1.1_3.0_1694265681109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_arabic_camelbert_msa_quarter","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_arabic_camelbert_msa_quarter", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_msa_quarter| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|406.3 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-quarter \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_sixteenth_ar.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_sixteenth_ar.md new file mode 100644 index 00000000000000..8954c6af5cf342 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_arabic_camelbert_msa_sixteenth_ar.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Arabic bert_base_arabic_camelbert_msa_sixteenth BertEmbeddings from CAMeL-Lab +author: John Snow Labs +name: bert_base_arabic_camelbert_msa_sixteenth +date: 2023-09-09 +tags: [bert, ar, open_source, fill_mask, onnx] +task: Embeddings +language: ar +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_msa_sixteenth` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_sixteenth_ar_5.1.1_3.0_1694265828638.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_sixteenth_ar_5.1.1_3.0_1694265828638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_arabic_camelbert_msa_sixteenth","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_arabic_camelbert_msa_sixteenth", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_msa_sixteenth| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|ar| +|Size:|406.4 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_cased_finetuned_mrpc_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_cased_finetuned_mrpc_en.md new file mode 100644 index 00000000000000..f8489fc55c6d06 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_cased_finetuned_mrpc_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_cased_finetuned_mrpc BertEmbeddings from huggingface +author: John Snow Labs +name: bert_base_cased_finetuned_mrpc +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_mrpc` is a English model originally trained by huggingface. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_mrpc_en_5.1.1_3.0_1694258661421.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_mrpc_en_5.1.1_3.0_1694258661421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_cased_finetuned_mrpc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_cased_finetuned_mrpc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetuned_mrpc| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|403.6 MB| + +## References + +https://huggingface.co/bert-base-cased-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_cnndm_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_cnndm_en.md new file mode 100644 index 00000000000000..cb5f347c371570 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_cnndm_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_cnndm BertEmbeddings from Aktsvigun +author: John Snow Labs +name: bert_base_cnndm +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cnndm` is a English model originally trained by Aktsvigun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cnndm_en_5.1.1_3.0_1694284674309.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cnndm_en_5.1.1_3.0_1694284674309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_cnndm","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_cnndm", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cnndm| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/Aktsvigun/bert-base-cnndm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_ct_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_ct_en.md new file mode 100644 index 00000000000000..3cd78134be5f60 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_ct_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_ct BertEmbeddings from Contrastive-Tension +author: John Snow Labs +name: bert_base_ct +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_ct` is a English model originally trained by Contrastive-Tension. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_ct_en_5.1.1_3.0_1694266339519.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_ct_en_5.1.1_3.0_1694266339519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_ct","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_ct", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_ct| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/Contrastive-Tension/BERT-Base-CT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_german_dbmdz_cased_de.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_german_dbmdz_cased_de.md new file mode 100644 index 00000000000000..225a4eefd0ccce --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_german_dbmdz_cased_de.md @@ -0,0 +1,93 @@ +--- +layout: model +title: German bert_base_german_dbmdz_cased BertEmbeddings from huggingface +author: John Snow Labs +name: bert_base_german_dbmdz_cased +date: 2023-09-09 +tags: [bert, de, open_source, fill_mask, onnx] +task: Embeddings +language: de +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_dbmdz_cased` is a German model originally trained by huggingface. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_dbmdz_cased_de_5.1.1_3.0_1694258795026.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_dbmdz_cased_de_5.1.1_3.0_1694258795026.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_german_dbmdz_cased","de") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_german_dbmdz_cased", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_german_dbmdz_cased| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|de| +|Size:|409.9 MB| + +## References + +https://huggingface.co/bert-base-german-dbmdz-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_german_dbmdz_uncased_de.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_german_dbmdz_uncased_de.md new file mode 100644 index 00000000000000..dd015644b96b61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_german_dbmdz_uncased_de.md @@ -0,0 +1,93 @@ +--- +layout: model +title: German bert_base_german_dbmdz_uncased BertEmbeddings from huggingface +author: John Snow Labs +name: bert_base_german_dbmdz_uncased +date: 2023-09-09 +tags: [bert, de, open_source, fill_mask, onnx] +task: Embeddings +language: de +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_dbmdz_uncased` is a German model originally trained by huggingface. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_dbmdz_uncased_de_5.1.1_3.0_1694258923096.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_dbmdz_uncased_de_5.1.1_3.0_1694258923096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_german_dbmdz_uncased","de") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_german_dbmdz_uncased", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_german_dbmdz_uncased| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|de| +|Size:|409.9 MB| + +## References + +https://huggingface.co/bert-base-german-dbmdz-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_irish_cased_v1_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_irish_cased_v1_en.md new file mode 100644 index 00000000000000..112ecf1c8f349e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_irish_cased_v1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_irish_cased_v1 BertEmbeddings from DCU-NLP +author: John Snow Labs +name: bert_base_irish_cased_v1 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_irish_cased_v1` is a English model originally trained by DCU-NLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_irish_cased_v1_en_5.1.1_3.0_1694267227315.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_irish_cased_v1_en_5.1.1_3.0_1694267227315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_irish_cased_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_irish_cased_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_irish_cased_v1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/DCU-NLP/bert-base-irish-cased-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_dholuo_xx.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_dholuo_xx.md new file mode 100644 index 00000000000000..655e943e52ecb9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_dholuo_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_dholuo BertEmbeddings from Davlan +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_dholuo +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_dholuo` is a Multilingual model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_dholuo_xx_5.1.1_3.0_1694278951025.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_dholuo_xx_5.1.1_3.0_1694278951025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_multilingual_cased_finetuned_dholuo","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_multilingual_cased_finetuned_dholuo", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_dholuo| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|665.0 MB| + +## References + +https://huggingface.co/Davlan/bert-base-multilingual-cased-finetuned-luo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_hausa_xx.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_hausa_xx.md new file mode 100644 index 00000000000000..149ed07c2c64ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_hausa_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_hausa BertEmbeddings from Davlan +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_hausa +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_hausa` is a Multilingual model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_hausa_xx_5.1.1_3.0_1694278252314.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_hausa_xx_5.1.1_3.0_1694278252314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_multilingual_cased_finetuned_hausa","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_multilingual_cased_finetuned_hausa", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_hausa| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|664.4 MB| + +## References + +https://huggingface.co/Davlan/bert-base-multilingual-cased-finetuned-hausa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_igbo_xx.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_igbo_xx.md new file mode 100644 index 00000000000000..0e4a6b4a957421 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_igbo_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_igbo BertEmbeddings from Davlan +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_igbo +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_igbo` is a Multilingual model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_igbo_xx_5.1.1_3.0_1694278402439.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_igbo_xx_5.1.1_3.0_1694278402439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_multilingual_cased_finetuned_igbo","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_multilingual_cased_finetuned_igbo", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_igbo| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|665.0 MB| + +## References + +https://huggingface.co/Davlan/bert-base-multilingual-cased-finetuned-igbo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_kinyarwanda_xx.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_kinyarwanda_xx.md new file mode 100644 index 00000000000000..957c00f8f8fdda --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_kinyarwanda_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_kinyarwanda BertEmbeddings from Davlan +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_kinyarwanda +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_kinyarwanda` is a Multilingual model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_kinyarwanda_xx_5.1.1_3.0_1694278577489.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_kinyarwanda_xx_5.1.1_3.0_1694278577489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_multilingual_cased_finetuned_kinyarwanda","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_multilingual_cased_finetuned_kinyarwanda", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_kinyarwanda| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|665.0 MB| + +## References + +https://huggingface.co/Davlan/bert-base-multilingual-cased-finetuned-kinyarwanda \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_luganda_xx.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_luganda_xx.md new file mode 100644 index 00000000000000..c46ab88595d621 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_luganda_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_luganda BertEmbeddings from Davlan +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_luganda +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_luganda` is a Multilingual model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_luganda_xx_5.1.1_3.0_1694278771746.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_luganda_xx_5.1.1_3.0_1694278771746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_multilingual_cased_finetuned_luganda","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_multilingual_cased_finetuned_luganda", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_luganda| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|665.0 MB| + +## References + +https://huggingface.co/Davlan/bert-base-multilingual-cased-finetuned-luganda \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_naija_xx.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_naija_xx.md new file mode 100644 index 00000000000000..421d7091f94175 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_naija_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_naija BertEmbeddings from Davlan +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_naija +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_naija` is a Multilingual model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_naija_xx_5.1.1_3.0_1694279152866.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_naija_xx_5.1.1_3.0_1694279152866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_multilingual_cased_finetuned_naija","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_multilingual_cased_finetuned_naija", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_naija| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|665.0 MB| + +## References + +https://huggingface.co/Davlan/bert-base-multilingual-cased-finetuned-naija \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_swahili_xx.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_swahili_xx.md new file mode 100644 index 00000000000000..269a10c63d7aef --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_swahili_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_swahili BertEmbeddings from Davlan +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_swahili +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_swahili` is a Multilingual model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_swahili_xx_5.1.1_3.0_1694279327334.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_swahili_xx_5.1.1_3.0_1694279327334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_multilingual_cased_finetuned_swahili","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_multilingual_cased_finetuned_swahili", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_swahili| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|664.1 MB| + +## References + +https://huggingface.co/Davlan/bert-base-multilingual-cased-finetuned-swahili \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_wolof_xx.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_wolof_xx.md new file mode 100644 index 00000000000000..6e5d0c0b946af8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_wolof_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_wolof BertEmbeddings from Davlan +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_wolof +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_wolof` is a Multilingual model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_wolof_xx_5.1.1_3.0_1694279557140.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_wolof_xx_5.1.1_3.0_1694279557140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_multilingual_cased_finetuned_wolof","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_multilingual_cased_finetuned_wolof", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_wolof| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|665.0 MB| + +## References + +https://huggingface.co/Davlan/bert-base-multilingual-cased-finetuned-wolof \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_yoruba_xx.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_yoruba_xx.md new file mode 100644 index 00000000000000..9e9d21f5fe7c9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_multilingual_cased_finetuned_yoruba_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_yoruba BertEmbeddings from Davlan +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_yoruba +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_yoruba` is a Multilingual model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_yoruba_xx_5.1.1_3.0_1694279730284.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_yoruba_xx_5.1.1_3.0_1694279730284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_multilingual_cased_finetuned_yoruba","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_multilingual_cased_finetuned_yoruba", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_yoruba| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|665.0 MB| + +## References + +https://huggingface.co/Davlan/bert-base-multilingual-cased-finetuned-yoruba \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_nli_ct_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_nli_ct_en.md new file mode 100644 index 00000000000000..1eafc57ae39a42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_nli_ct_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_nli_ct BertEmbeddings from Contrastive-Tension +author: John Snow Labs +name: bert_base_nli_ct +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_nli_ct` is a English model originally trained by Contrastive-Tension. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_nli_ct_en_5.1.1_3.0_1694266469274.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_nli_ct_en_5.1.1_3.0_1694266469274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_nli_ct","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_nli_ct", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_nli_ct| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/Contrastive-Tension/BERT-Base-NLI-CT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_parsbert_uncased_finetuned_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_parsbert_uncased_finetuned_en.md new file mode 100644 index 00000000000000..7a6ba5464ba044 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_parsbert_uncased_finetuned_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_parsbert_uncased_finetuned BertEmbeddings from Ashkanmh +author: John Snow Labs +name: bert_base_parsbert_uncased_finetuned +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_parsbert_uncased_finetuned` is a English model originally trained by Ashkanmh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_parsbert_uncased_finetuned_en_5.1.1_3.0_1694261097567.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_parsbert_uncased_finetuned_en_5.1.1_3.0_1694261097567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_parsbert_uncased_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_parsbert_uncased_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_parsbert_uncased_finetuned| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|606.4 MB| + +## References + +https://huggingface.co/Ashkanmh/bert-base-parsbert-uncased-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_portuguese_cased_test_server_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_portuguese_cased_test_server_en.md new file mode 100644 index 00000000000000..2b291b6de7d25f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_portuguese_cased_test_server_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_portuguese_cased_test_server BertEmbeddings from tiagoseca +author: John Snow Labs +name: bert_base_portuguese_cased_test_server +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_portuguese_cased_test_server` is a English model originally trained by tiagoseca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_cased_test_server_en_5.1.1_3.0_1694282814248.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_cased_test_server_en_5.1.1_3.0_1694282814248.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_portuguese_cased_test_server","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_portuguese_cased_test_server", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_portuguese_cased_test_server| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/tiagoseca/bert-base-portuguese-cased-test-server \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_pubmed_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_pubmed_en.md new file mode 100644 index 00000000000000..e0e99afb07122a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_pubmed_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_pubmed BertEmbeddings from Aktsvigun +author: John Snow Labs +name: bert_base_pubmed +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_pubmed` is a English model originally trained by Aktsvigun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_pubmed_en_5.1.1_3.0_1694284978014.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_pubmed_en_5.1.1_3.0_1694284978014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_pubmed","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_pubmed", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_pubmed| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/Aktsvigun/bert-base-pubmed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_dish_descriptions_128_0.5m_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_dish_descriptions_128_0.5m_en.md new file mode 100644 index 00000000000000..2e110d21a00bd6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_dish_descriptions_128_0.5m_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_dish_descriptions_128_0.5m BertEmbeddings from abhilashawasthi +author: John Snow Labs +name: bert_base_uncased_dish_descriptions_128_0.5m +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_dish_descriptions_128_0.5m` is a English model originally trained by abhilashawasthi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_dish_descriptions_128_0.5m_en_5.1.1_3.0_1694267375313.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_dish_descriptions_128_0.5m_en_5.1.1_3.0_1694267375313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_dish_descriptions_128_0.5m","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_dish_descriptions_128_0.5m", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_dish_descriptions_128_0.5m| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/abhilashawasthi/bert-base-uncased_dish_descriptions_128_0.5M \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_dish_descriptions_128_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_dish_descriptions_128_en.md new file mode 100644 index 00000000000000..b4649ff02aed7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_dish_descriptions_128_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_dish_descriptions_128 BertEmbeddings from abhilashawasthi +author: John Snow Labs +name: bert_base_uncased_dish_descriptions_128 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_dish_descriptions_128` is a English model originally trained by abhilashawasthi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_dish_descriptions_128_en_5.1.1_3.0_1694267255228.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_dish_descriptions_128_en_5.1.1_3.0_1694267255228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_dish_descriptions_128","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_dish_descriptions_128", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_dish_descriptions_128| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/abhilashawasthi/bert-base-uncased_dish_descriptions_128 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_fined_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_fined_en.md new file mode 100644 index 00000000000000..105aab3e571653 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_fined_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_fined BertEmbeddings from WaylonZHANG +author: John Snow Labs +name: bert_base_uncased_fined +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_fined` is a English model originally trained by WaylonZHANG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fined_en_5.1.1_3.0_1694278266100.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fined_en_5.1.1_3.0_1694278266100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_fined","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_fined", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_fined| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/WaylonZHANG/bert_base_uncased_fined \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetune_security_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetune_security_en.md new file mode 100644 index 00000000000000..ab915d7a7e8509 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetune_security_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_finetune_security BertEmbeddings from forcorpus +author: John Snow Labs +name: bert_base_uncased_finetune_security +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_security` is a English model originally trained by forcorpus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_security_en_5.1.1_3.0_1694283220765.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_security_en_5.1.1_3.0_1694283220765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_finetune_security","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_finetune_security", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetune_security| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/forcorpus/bert-base-uncased-finetune-security \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies_en.md new file mode 100644 index 00000000000000..b4be4993f6f65d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies BertEmbeddings from ietz +author: John Snow Labs +name: bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies` is a English model originally trained by ietz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies_en_5.1.1_3.0_1694266366291.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies_en_5.1.1_3.0_1694266366291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_jira_hyperledger_issue_titles_and_bodies| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/ietz/bert-base-uncased-finetuned-jira-hyperledger-issue-titles-and-bodies \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies_en.md new file mode 100644 index 00000000000000..57f22521a24775 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies BertEmbeddings from ietz +author: John Snow Labs +name: bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies` is a English model originally trained by ietz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies_en_5.1.1_3.0_1694266491902.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies_en_5.1.1_3.0_1694266491902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_jira_inteldaos_issue_titles_and_bodies| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/ietz/bert-base-uncased-finetuned-jira-inteldaos-issue-titles-and-bodies \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies_en.md new file mode 100644 index 00000000000000..ade00fc8ff535c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies BertEmbeddings from ietz +author: John Snow Labs +name: bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies` is a English model originally trained by ietz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies_en_5.1.1_3.0_1694266630282.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies_en_5.1.1_3.0_1694266630282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_jira_jira_issue_titles_and_bodies| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/ietz/bert-base-uncased-finetuned-jira-jira-issue-titles-and-bodies \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies_en.md new file mode 100644 index 00000000000000..d0c1d0e0c61841 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies BertEmbeddings from ietz +author: John Snow Labs +name: bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies` is a English model originally trained by ietz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies_en_5.1.1_3.0_1694266778727.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies_en_5.1.1_3.0_1694266778727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_jira_qt_issue_titles_and_bodies| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/ietz/bert-base-uncased-finetuned-jira-qt-issue-titles-and-bodies \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_issues_128_susnato_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_issues_128_susnato_en.md new file mode 100644 index 00000000000000..320f013ae433a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_issues_128_susnato_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_issues_128_susnato BertEmbeddings from susnato +author: John Snow Labs +name: bert_base_uncased_issues_128_susnato +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_susnato` is a English model originally trained by susnato. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_susnato_en_5.1.1_3.0_1694259405770.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_susnato_en_5.1.1_3.0_1694259405770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_issues_128_susnato","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_issues_128_susnato", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_issues_128_susnato| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/susnato/bert-base-uncased-issues-128 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_issues_128_tanviraumi_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_issues_128_tanviraumi_en.md new file mode 100644 index 00000000000000..61d67ec04e8d27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_issues_128_tanviraumi_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_issues_128_tanviraumi BertEmbeddings from tanviraumi +author: John Snow Labs +name: bert_base_uncased_issues_128_tanviraumi +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_tanviraumi` is a English model originally trained by tanviraumi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_tanviraumi_en_5.1.1_3.0_1694283686698.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_tanviraumi_en_5.1.1_3.0_1694283686698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_issues_128_tanviraumi","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_issues_128_tanviraumi", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_issues_128_tanviraumi| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/tanviraumi/bert-base-uncased-issues-128 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_semeval2014_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_semeval2014_en.md new file mode 100644 index 00000000000000..8ade600e6871f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_semeval2014_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_semeval2014 BertEmbeddings from StevenLimcorn +author: John Snow Labs +name: bert_base_uncased_semeval2014 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_semeval2014` is a English model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_semeval2014_en_5.1.1_3.0_1694260733939.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_semeval2014_en_5.1.1_3.0_1694260733939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_semeval2014","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_semeval2014", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_semeval2014| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.0 MB| + +## References + +https://huggingface.co/StevenLimcorn/bert-base-uncased-semeval2014 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_zhibinhong_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_zhibinhong_en.md new file mode 100644 index 00000000000000..62401ec1c801ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_base_uncased_zhibinhong_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_base_uncased_zhibinhong BertEmbeddings from Zhibinhong +author: John Snow Labs +name: bert_base_uncased_zhibinhong +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_zhibinhong` is a English model originally trained by Zhibinhong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_zhibinhong_en_5.1.1_3.0_1694278831256.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_zhibinhong_en_5.1.1_3.0_1694278831256.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_base_uncased_zhibinhong","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_base_uncased_zhibinhong", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_zhibinhong| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/Zhibinhong/bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_finetuning_test1227_hug_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_finetuning_test1227_hug_en.md new file mode 100644 index 00000000000000..bc672cd4755582 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_finetuning_test1227_hug_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_finetuning_test1227_hug BertEmbeddings from junzai +author: John Snow Labs +name: bert_finetuning_test1227_hug +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuning_test1227_hug` is a English model originally trained by junzai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuning_test1227_hug_en_5.1.1_3.0_1694284329023.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuning_test1227_hug_en_5.1.1_3.0_1694284329023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_finetuning_test1227_hug","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_finetuning_test1227_hug", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuning_test1227_hug| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/junzai/bert_finetuning_test1227_hug \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_finetuning_test_hug_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_finetuning_test_hug_en.md new file mode 100644 index 00000000000000..35e6d3797193ba --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_finetuning_test_hug_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_finetuning_test_hug BertEmbeddings from junzai +author: John Snow Labs +name: bert_finetuning_test_hug +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuning_test_hug` is a English model originally trained by junzai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuning_test_hug_en_5.1.1_3.0_1694284465366.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuning_test_hug_en_5.1.1_3.0_1694284465366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_finetuning_test_hug","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_finetuning_test_hug", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuning_test_hug| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/junzai/bert_finetuning_test_hug \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_funting_test_ai10_junzai_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_funting_test_ai10_junzai_en.md new file mode 100644 index 00000000000000..1e5dc78bc4c5f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_funting_test_ai10_junzai_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_funting_test_ai10_junzai BertEmbeddings from junzai +author: John Snow Labs +name: bert_funting_test_ai10_junzai +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_funting_test_ai10_junzai` is a English model originally trained by junzai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_funting_test_ai10_junzai_en_5.1.1_3.0_1694284595771.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_funting_test_ai10_junzai_en_5.1.1_3.0_1694284595771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_funting_test_ai10_junzai","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_funting_test_ai10_junzai", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_funting_test_ai10_junzai| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/junzai/bert_funting_test_ai10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_gb_2021_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_gb_2021_en.md new file mode 100644 index 00000000000000..1e05c2f55e62cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_gb_2021_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_gb_2021 BertEmbeddings from mossaic-candle +author: John Snow Labs +name: bert_gb_2021 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_gb_2021` is a English model originally trained by mossaic-candle. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_gb_2021_en_5.1.1_3.0_1694265192765.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_gb_2021_en_5.1.1_3.0_1694265192765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_gb_2021","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_gb_2021", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_gb_2021| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|258.6 MB| + +## References + +https://huggingface.co/mossaic-candle/bert-gb-2021 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_hateracism90000_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_hateracism90000_en.md new file mode 100644 index 00000000000000..aa59d80094ddeb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_hateracism90000_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_hateracism90000 BertEmbeddings from MutazYoune +author: John Snow Labs +name: bert_hateracism90000 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_hateracism90000` is a English model originally trained by MutazYoune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_hateracism90000_en_5.1.1_3.0_1694278823263.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_hateracism90000_en_5.1.1_3.0_1694278823263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_hateracism90000","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_hateracism90000", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_hateracism90000| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.3 MB| + +## References + +https://huggingface.co/MutazYoune/bert_hateracism90000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8_en.md new file mode 100644 index 00000000000000..34ed104b7d5d82 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8 BertEmbeddings from jojoUla +author: John Snow Labs +name: bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8_en_5.1.1_3.0_1694258979428.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8_en_5.1.1_3.0_1694258979428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_8| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9_en.md new file mode 100644 index 00000000000000..aa78adbc9c3e68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9 BertEmbeddings from jojoUla +author: John Snow Labs +name: bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9_en_5.1.1_3.0_1694259240953.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9_en_5.1.1_3.0_1694259240953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_9| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0_en.md new file mode 100644 index 00000000000000..c29abd12730a56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0 BertEmbeddings from jojoUla +author: John Snow Labs +name: bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0_en_5.1.1_3.0_1694280291790.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0_en_5.1.1_3.0_1694280291790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_0| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2_en.md new file mode 100644 index 00000000000000..736e65d5738670 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2 BertEmbeddings from jojoUla +author: John Snow Labs +name: bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2_en_5.1.1_3.0_1694282816860.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2_en_5.1.1_3.0_1694282816860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3_en.md new file mode 100644 index 00000000000000..78ce6d3556d706 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3 BertEmbeddings from jojoUla +author: John Snow Labs +name: bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3_en_5.1.1_3.0_1694283082305.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3_en_5.1.1_3.0_1694283082305.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_3| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4_en.md new file mode 100644 index 00000000000000..d5628516f2eb61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4 BertEmbeddings from jojoUla +author: John Snow Labs +name: bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4_en_5.1.1_3.0_1694283342684.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4_en_5.1.1_3.0_1694283342684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_4| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5_en.md new file mode 100644 index 00000000000000..feec7fe169dbd1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5 BertEmbeddings from jojoUla +author: John Snow Labs +name: bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5_en_5.1.1_3.0_1694284168464.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5_en_5.1.1_3.0_1694284168464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_5| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6_en.md new file mode 100644 index 00000000000000..8e90a33d05ac78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6 BertEmbeddings from jojoUla +author: John Snow Labs +name: bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6_en_5.1.1_3.0_1694284456608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6_en_5.1.1_3.0_1694284456608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_6| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7_en.md new file mode 100644 index 00000000000000..afdd80eaec72b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7 BertEmbeddings from jojoUla +author: John Snow Labs +name: bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7_en_5.1.1_3.0_1694284718630.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7_en_5.1.1_3.0_1694284718630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_7| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8_en.md new file mode 100644 index 00000000000000..8528046ec74e1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8 BertEmbeddings from jojoUla +author: John Snow Labs +name: bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8_en_5.1.1_3.0_1694284970323.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8_en_5.1.1_3.0_1694284970323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_8| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_whole_word_masking_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_whole_word_masking_en.md new file mode 100644 index 00000000000000..7a5098c64d7ad6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_cased_whole_word_masking_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_cased_whole_word_masking BertEmbeddings from huggingface +author: John Snow Labs +name: bert_large_cased_whole_word_masking +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_whole_word_masking` is a English model originally trained by huggingface. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_whole_word_masking_en_5.1.1_3.0_1694259195109.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_whole_word_masking_en_5.1.1_3.0_1694259195109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_cased_whole_word_masking","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_cased_whole_word_masking", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_whole_word_masking| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/bert-large-cased-whole-word-masking \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_ct_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_ct_en.md new file mode 100644 index 00000000000000..1e073ff2832ad7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_ct_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_ct BertEmbeddings from Contrastive-Tension +author: John Snow Labs +name: bert_large_ct +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_ct` is a English model originally trained by Contrastive-Tension. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_ct_en_5.1.1_3.0_1694266770807.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_ct_en_5.1.1_3.0_1694266770807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_ct","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_ct", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_ct| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Contrastive-Tension/BERT-Large-CT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_nli_ct_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_nli_ct_en.md new file mode 100644 index 00000000000000..269fab63ec9a09 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_nli_ct_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_nli_ct BertEmbeddings from Contrastive-Tension +author: John Snow Labs +name: bert_large_nli_ct +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_nli_ct` is a English model originally trained by Contrastive-Tension. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_nli_ct_en_5.1.1_3.0_1694267030145.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_nli_ct_en_5.1.1_3.0_1694267030145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_nli_ct","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_nli_ct", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_nli_ct| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Contrastive-Tension/BERT-Large-NLI-CT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_portuguese_cased_legal_mlm_pt.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_portuguese_cased_legal_mlm_pt.md new file mode 100644 index 00000000000000..b65c271db09561 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_portuguese_cased_legal_mlm_pt.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Portuguese bert_large_portuguese_cased_legal_mlm BertEmbeddings from stjiris +author: John Snow Labs +name: bert_large_portuguese_cased_legal_mlm +date: 2023-09-09 +tags: [bert, pt, open_source, fill_mask, onnx] +task: Embeddings +language: pt +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_portuguese_cased_legal_mlm` is a Portuguese model originally trained by stjiris. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_portuguese_cased_legal_mlm_pt_5.1.1_3.0_1694284288827.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_portuguese_cased_legal_mlm_pt_5.1.1_3.0_1694284288827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_portuguese_cased_legal_mlm","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_portuguese_cased_legal_mlm", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_portuguese_cased_legal_mlm| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|pt| +|Size:|1.2 GB| + +## References + +https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-mlm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_portuguese_cased_legal_tsdae_pt.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_portuguese_cased_legal_tsdae_pt.md new file mode 100644 index 00000000000000..481a8fb59f782a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_portuguese_cased_legal_tsdae_pt.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Portuguese bert_large_portuguese_cased_legal_tsdae BertEmbeddings from stjiris +author: John Snow Labs +name: bert_large_portuguese_cased_legal_tsdae +date: 2023-09-09 +tags: [bert, pt, open_source, fill_mask, onnx] +task: Embeddings +language: pt +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_portuguese_cased_legal_tsdae` is a Portuguese model originally trained by stjiris. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_portuguese_cased_legal_tsdae_pt_5.1.1_3.0_1694280251721.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_portuguese_cased_legal_tsdae_pt_5.1.1_3.0_1694280251721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_portuguese_cased_legal_tsdae","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_portuguese_cased_legal_tsdae", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_portuguese_cased_legal_tsdae| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|pt| +|Size:|1.2 GB| + +## References + +https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-tsdae \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_facebook_election_ads_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_facebook_election_ads_en.md new file mode 100644 index 00000000000000..641ffc3a53bf4a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_facebook_election_ads_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_uncased_facebook_election_ads BertEmbeddings from StevenLimcorn +author: John Snow Labs +name: bert_large_uncased_facebook_election_ads +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_facebook_election_ads` is a English model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_facebook_election_ads_en_5.1.1_3.0_1694278584320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_facebook_election_ads_en_5.1.1_3.0_1694278584320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_uncased_facebook_election_ads","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_uncased_facebook_election_ads", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_facebook_election_ads| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/StevenLimcorn/bert-large-uncased-facebook-election-ads \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2014_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2014_en.md new file mode 100644 index 00000000000000..85f86123fd8f8d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2014_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_uncased_semeval2014 BertEmbeddings from StevenLimcorn +author: John Snow Labs +name: bert_large_uncased_semeval2014 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_semeval2014` is a English model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2014_en_5.1.1_3.0_1694261000799.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2014_en_5.1.1_3.0_1694261000799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_uncased_semeval2014","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_uncased_semeval2014", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_semeval2014| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/StevenLimcorn/bert-large-uncased-semeval2014 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2014_laptops_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2014_laptops_en.md new file mode 100644 index 00000000000000..955dcedb8ddbf5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2014_laptops_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_uncased_semeval2014_laptops BertEmbeddings from StevenLimcorn +author: John Snow Labs +name: bert_large_uncased_semeval2014_laptops +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_semeval2014_laptops` is a English model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2014_laptops_en_5.1.1_3.0_1694265613724.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2014_laptops_en_5.1.1_3.0_1694265613724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_uncased_semeval2014_laptops","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_uncased_semeval2014_laptops", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_semeval2014_laptops| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/StevenLimcorn/bert-large-uncased-semeval2014-laptops \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2014_restaurants_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2014_restaurants_en.md new file mode 100644 index 00000000000000..7872f10823545d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2014_restaurants_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_uncased_semeval2014_restaurants BertEmbeddings from StevenLimcorn +author: John Snow Labs +name: bert_large_uncased_semeval2014_restaurants +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_semeval2014_restaurants` is a English model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2014_restaurants_en_5.1.1_3.0_1694265347275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2014_restaurants_en_5.1.1_3.0_1694265347275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_uncased_semeval2014_restaurants","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_uncased_semeval2014_restaurants", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_semeval2014_restaurants| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/StevenLimcorn/bert-large-uncased-semeval2014-restaurants \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2015_laptops_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2015_laptops_en.md new file mode 100644 index 00000000000000..55537fe49f637b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2015_laptops_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_uncased_semeval2015_laptops BertEmbeddings from StevenLimcorn +author: John Snow Labs +name: bert_large_uncased_semeval2015_laptops +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_semeval2015_laptops` is a English model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2015_laptops_en_5.1.1_3.0_1694266817614.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2015_laptops_en_5.1.1_3.0_1694266817614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_uncased_semeval2015_laptops","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_uncased_semeval2015_laptops", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_semeval2015_laptops| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/StevenLimcorn/bert-large-uncased-semeval2015-laptops \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2015_restaurants_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2015_restaurants_en.md new file mode 100644 index 00000000000000..4ecf75d897841d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2015_restaurants_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_uncased_semeval2015_restaurants BertEmbeddings from StevenLimcorn +author: John Snow Labs +name: bert_large_uncased_semeval2015_restaurants +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_semeval2015_restaurants` is a English model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2015_restaurants_en_5.1.1_3.0_1694266273762.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2015_restaurants_en_5.1.1_3.0_1694266273762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_uncased_semeval2015_restaurants","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_uncased_semeval2015_restaurants", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_semeval2015_restaurants| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/StevenLimcorn/bert-large-uncased-semeval2015-restaurants \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2016_laptops_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2016_laptops_en.md new file mode 100644 index 00000000000000..fa9b772ccdcb54 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2016_laptops_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_uncased_semeval2016_laptops BertEmbeddings from StevenLimcorn +author: John Snow Labs +name: bert_large_uncased_semeval2016_laptops +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_semeval2016_laptops` is a English model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2016_laptops_en_5.1.1_3.0_1694267362070.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2016_laptops_en_5.1.1_3.0_1694267362070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_uncased_semeval2016_laptops","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_uncased_semeval2016_laptops", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_semeval2016_laptops| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/StevenLimcorn/bert-large-uncased-semeval2016-laptops \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2016_restaurants_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2016_restaurants_en.md new file mode 100644 index 00000000000000..3dfb2372eafc23 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_semeval2016_restaurants_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_uncased_semeval2016_restaurants BertEmbeddings from StevenLimcorn +author: John Snow Labs +name: bert_large_uncased_semeval2016_restaurants +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_semeval2016_restaurants` is a English model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2016_restaurants_en_5.1.1_3.0_1694267083539.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_semeval2016_restaurants_en_5.1.1_3.0_1694267083539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_uncased_semeval2016_restaurants","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_uncased_semeval2016_restaurants", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_semeval2016_restaurants| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/StevenLimcorn/bert-large-uncased-semeval2016-restaurants \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_whole_word_masking_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_whole_word_masking_en.md new file mode 100644 index 00000000000000..134d8c8bab6e0a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_large_uncased_whole_word_masking_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_large_uncased_whole_word_masking BertEmbeddings from huggingface +author: John Snow Labs +name: bert_large_uncased_whole_word_masking +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking` is a English model originally trained by huggingface. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_en_5.1.1_3.0_1694259457325.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_en_5.1.1_3.0_1694259457325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_large_uncased_whole_word_masking","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_large_uncased_whole_word_masking", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_whole_word_masking| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/bert-large-uncased-whole-word-masking \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_nlp_project_news_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_nlp_project_news_en.md new file mode 100644 index 00000000000000..75d00146e0681c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_nlp_project_news_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_nlp_project_news BertEmbeddings from jestemleon +author: John Snow Labs +name: bert_nlp_project_news +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_nlp_project_news` is a English model originally trained by jestemleon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_nlp_project_news_en_5.1.1_3.0_1694260118481.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_nlp_project_news_en_5.1.1_3.0_1694260118481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_nlp_project_news","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_nlp_project_news", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_nlp_project_news| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/jestemleon/bert-nlp-project-news \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_patent_reference_extraction_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_patent_reference_extraction_en.md new file mode 100644 index 00000000000000..42c962ffcd6101 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_patent_reference_extraction_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_patent_reference_extraction BertEmbeddings from kaesve +author: John Snow Labs +name: bert_patent_reference_extraction +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_patent_reference_extraction` is a English model originally trained by kaesve. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_patent_reference_extraction_en_5.1.1_3.0_1694284932215.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_patent_reference_extraction_en_5.1.1_3.0_1694284932215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_patent_reference_extraction","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_patent_reference_extraction", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_patent_reference_extraction| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|403.6 MB| + +## References + +https://huggingface.co/kaesve/BERT_patent_reference_extraction \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_racism15_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_racism15_en.md new file mode 100644 index 00000000000000..e9e3efe744910e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_racism15_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_racism15 BertEmbeddings from MutazYoune +author: John Snow Labs +name: bert_racism15 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_racism15` is a English model originally trained by MutazYoune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_racism15_en_5.1.1_3.0_1694266961024.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_racism15_en_5.1.1_3.0_1694266961024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_racism15","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_racism15", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_racism15| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.2 MB| + +## References + +https://huggingface.co/MutazYoune/BERT_racism15 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_racism_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_racism_en.md new file mode 100644 index 00000000000000..1a10893b096360 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_racism_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_racism BertEmbeddings from MutazYoune +author: John Snow Labs +name: bert_racism +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_racism` is a English model originally trained by MutazYoune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_racism_en_5.1.1_3.0_1694266727516.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_racism_en_5.1.1_3.0_1694266727516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_racism","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_racism", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_racism| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.1 MB| + +## References + +https://huggingface.co/MutazYoune/BERT_racism \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_random_weights_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_random_weights_en.md new file mode 100644 index 00000000000000..eee950bc418190 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_random_weights_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_random_weights BertEmbeddings from ashraq +author: John Snow Labs +name: bert_random_weights +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_random_weights` is a English model originally trained by ashraq. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_random_weights_en_5.1.1_3.0_1694265078198.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_random_weights_en_5.1.1_3.0_1694265078198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_random_weights","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_random_weights", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_random_weights| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.8 GB| + +## References + +https://huggingface.co/ashraq/bert-random-weights \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_sparql_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_sparql_en.md new file mode 100644 index 00000000000000..0a85fafc6f1dc5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_sparql_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_sparql BertEmbeddings from JulienRPA +author: John Snow Labs +name: bert_sparql +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sparql` is a English model originally trained by JulienRPA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sparql_en_5.1.1_3.0_1694279133283.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sparql_en_5.1.1_3.0_1694279133283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_sparql","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_sparql", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sparql| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|413.6 MB| + +## References + +https://huggingface.co/JulienRPA/BERT_SPARQL \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_srb_base_cased_oscar_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_srb_base_cased_oscar_en.md new file mode 100644 index 00000000000000..dd2fa004633eba --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_srb_base_cased_oscar_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_srb_base_cased_oscar BertEmbeddings from Aleksandar +author: John Snow Labs +name: bert_srb_base_cased_oscar +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_srb_base_cased_oscar` is a English model originally trained by Aleksandar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_srb_base_cased_oscar_en_5.1.1_3.0_1694260821609.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_srb_base_cased_oscar_en_5.1.1_3.0_1694260821609.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_srb_base_cased_oscar","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_srb_base_cased_oscar", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_srb_base_cased_oscar| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|403.9 MB| + +## References + +https://huggingface.co/Aleksandar/bert-srb-base-cased-oscar \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_cased_tl.md b/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_cased_tl.md new file mode 100644 index 00000000000000..a6f876f661e217 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_cased_tl.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Tagalog bert_tagalog_base_cased BertEmbeddings from jcblaise +author: John Snow Labs +name: bert_tagalog_base_cased +date: 2023-09-09 +tags: [bert, tl, open_source, fill_mask, onnx] +task: Embeddings +language: tl +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tagalog_base_cased` is a Tagalog model originally trained by jcblaise. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tagalog_base_cased_tl_5.1.1_3.0_1694278808394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tagalog_base_cased_tl_5.1.1_3.0_1694278808394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_tagalog_base_cased","tl") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_tagalog_base_cased", "tl") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tagalog_base_cased| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|tl| +|Size:|406.9 MB| + +## References + +https://huggingface.co/jcblaise/bert-tagalog-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_cased_wwm_tl.md b/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_cased_wwm_tl.md new file mode 100644 index 00000000000000..5e3c837c6d007a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_cased_wwm_tl.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Tagalog bert_tagalog_base_cased_wwm BertEmbeddings from jcblaise +author: John Snow Labs +name: bert_tagalog_base_cased_wwm +date: 2023-09-09 +tags: [bert, tl, open_source, fill_mask, onnx] +task: Embeddings +language: tl +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tagalog_base_cased_wwm` is a Tagalog model originally trained by jcblaise. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tagalog_base_cased_wwm_tl_5.1.1_3.0_1694278641553.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tagalog_base_cased_wwm_tl_5.1.1_3.0_1694278641553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_tagalog_base_cased_wwm","tl") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_tagalog_base_cased_wwm", "tl") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tagalog_base_cased_wwm| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|tl| +|Size:|406.9 MB| + +## References + +https://huggingface.co/jcblaise/bert-tagalog-base-cased-WWM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_uncased_tl.md b/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_uncased_tl.md new file mode 100644 index 00000000000000..82b278c29a6f6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_uncased_tl.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Tagalog bert_tagalog_base_uncased BertEmbeddings from jcblaise +author: John Snow Labs +name: bert_tagalog_base_uncased +date: 2023-09-09 +tags: [bert, tl, open_source, fill_mask, onnx] +task: Embeddings +language: tl +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tagalog_base_uncased` is a Tagalog model originally trained by jcblaise. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tagalog_base_uncased_tl_5.1.1_3.0_1694279118482.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tagalog_base_uncased_tl_5.1.1_3.0_1694279118482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_tagalog_base_uncased","tl") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_tagalog_base_uncased", "tl") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tagalog_base_uncased| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|tl| +|Size:|406.9 MB| + +## References + +https://huggingface.co/jcblaise/bert-tagalog-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_uncased_wwm_tl.md b/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_uncased_wwm_tl.md new file mode 100644 index 00000000000000..5dcf7652d336f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_tagalog_base_uncased_wwm_tl.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Tagalog bert_tagalog_base_uncased_wwm BertEmbeddings from jcblaise +author: John Snow Labs +name: bert_tagalog_base_uncased_wwm +date: 2023-09-09 +tags: [bert, tl, open_source, fill_mask, onnx] +task: Embeddings +language: tl +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tagalog_base_uncased_wwm` is a Tagalog model originally trained by jcblaise. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tagalog_base_uncased_wwm_tl_5.1.1_3.0_1694278968293.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tagalog_base_uncased_wwm_tl_5.1.1_3.0_1694278968293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_tagalog_base_uncased_wwm","tl") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_tagalog_base_uncased_wwm", "tl") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tagalog_base_uncased_wwm| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|tl| +|Size:|406.9 MB| + +## References + +https://huggingface.co/jcblaise/bert-tagalog-base-uncased-WWM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_test_junzai_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_test_junzai_en.md new file mode 100644 index 00000000000000..a41496c98f9933 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_test_junzai_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_test_junzai BertEmbeddings from junzai +author: John Snow Labs +name: bert_test_junzai +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_test_junzai` is a English model originally trained by junzai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_test_junzai_en_5.1.1_3.0_1694284713154.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_test_junzai_en_5.1.1_3.0_1694284713154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_test_junzai","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_test_junzai", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_test_junzai| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/junzai/bert_test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_ucb_3_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_ucb_3_en.md new file mode 100644 index 00000000000000..fa1fabe6db1efd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_ucb_3_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_ucb_3 BertEmbeddings from Diegomejia +author: John Snow Labs +name: bert_ucb_3 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ucb_3` is a English model originally trained by Diegomejia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ucb_3_en_5.1.1_3.0_1694278278062.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ucb_3_en_5.1.1_3.0_1694278278062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_ucb_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_ucb_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ucb_3| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Diegomejia/bert-ucb-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bert_ucb_4_en.md b/docs/_posts/ahmedlone127/2023-09-09-bert_ucb_4_en.md new file mode 100644 index 00000000000000..b29a4c374e7b60 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bert_ucb_4_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bert_ucb_4 BertEmbeddings from Diegomejia +author: John Snow Labs +name: bert_ucb_4 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ucb_4` is a English model originally trained by Diegomejia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ucb_4_en_5.1.1_3.0_1694280320658.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ucb_4_en_5.1.1_3.0_1694280320658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bert_ucb_4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bert_ucb_4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ucb_4| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Diegomejia/bert-ucb-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bertimbau_large_fine_tuned_md_en.md b/docs/_posts/ahmedlone127/2023-09-09-bertimbau_large_fine_tuned_md_en.md new file mode 100644 index 00000000000000..92bba85958c954 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bertimbau_large_fine_tuned_md_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bertimbau_large_fine_tuned_md BertEmbeddings from AVSilva +author: John Snow Labs +name: bertimbau_large_fine_tuned_md +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertimbau_large_fine_tuned_md` is a English model originally trained by AVSilva. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertimbau_large_fine_tuned_md_en_5.1.1_3.0_1694259726163.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertimbau_large_fine_tuned_md_en_5.1.1_3.0_1694259726163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bertimbau_large_fine_tuned_md","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bertimbau_large_fine_tuned_md", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertimbau_large_fine_tuned_md| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/AVSilva/bertimbau-large-fine-tuned-md \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bertimbau_large_fine_tuned_sindhi_en.md b/docs/_posts/ahmedlone127/2023-09-09-bertimbau_large_fine_tuned_sindhi_en.md new file mode 100644 index 00000000000000..b47ebff72ea991 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bertimbau_large_fine_tuned_sindhi_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bertimbau_large_fine_tuned_sindhi BertEmbeddings from AVSilva +author: John Snow Labs +name: bertimbau_large_fine_tuned_sindhi +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertimbau_large_fine_tuned_sindhi` is a English model originally trained by AVSilva. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertimbau_large_fine_tuned_sindhi_en_5.1.1_3.0_1694259990408.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertimbau_large_fine_tuned_sindhi_en_5.1.1_3.0_1694259990408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bertimbau_large_fine_tuned_sindhi","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bertimbau_large_fine_tuned_sindhi", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertimbau_large_fine_tuned_sindhi| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/AVSilva/bertimbau-large-fine-tuned-sd \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bertunam_en.md b/docs/_posts/ahmedlone127/2023-09-09-bertunam_en.md new file mode 100644 index 00000000000000..eac5fd127acb8f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bertunam_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bertunam BertEmbeddings from benanxio +author: John Snow Labs +name: bertunam +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertunam` is a English model originally trained by benanxio. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertunam_en_5.1.1_3.0_1694259167797.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertunam_en_5.1.1_3.0_1694259167797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bertunam","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bertunam", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertunam| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/benanxio/BERTUNAM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-biodivbert_en.md b/docs/_posts/ahmedlone127/2023-09-09-biodivbert_en.md new file mode 100644 index 00000000000000..5f3fa527413705 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-biodivbert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English biodivbert BertEmbeddings from NoYo25 +author: John Snow Labs +name: biodivbert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biodivbert` is a English model originally trained by NoYo25. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biodivbert_en_5.1.1_3.0_1694264878557.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biodivbert_en_5.1.1_3.0_1694264878557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("biodivbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("biodivbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biodivbert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|403.6 MB| + +## References + +https://huggingface.co/NoYo25/BiodivBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-biomednlp_pubmedbert_large_uncased_abstract_en.md b/docs/_posts/ahmedlone127/2023-09-09-biomednlp_pubmedbert_large_uncased_abstract_en.md new file mode 100644 index 00000000000000..210bd2205e7880 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-biomednlp_pubmedbert_large_uncased_abstract_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English biomednlp_pubmedbert_large_uncased_abstract BertEmbeddings from microsoft +author: John Snow Labs +name: biomednlp_pubmedbert_large_uncased_abstract +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_pubmedbert_large_uncased_abstract` is a English model originally trained by microsoft. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_large_uncased_abstract_en_5.1.1_3.0_1694283092570.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_large_uncased_abstract_en_5.1.1_3.0_1694283092570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("biomednlp_pubmedbert_large_uncased_abstract","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("biomednlp_pubmedbert_large_uncased_abstract", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biomednlp_pubmedbert_large_uncased_abstract| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-large-uncased-abstract \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-bodo_bert_mlm_base_article_en.md b/docs/_posts/ahmedlone127/2023-09-09-bodo_bert_mlm_base_article_en.md new file mode 100644 index 00000000000000..cf619bdcc1e965 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-bodo_bert_mlm_base_article_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English bodo_bert_mlm_base_article BertEmbeddings from alayaran +author: John Snow Labs +name: bodo_bert_mlm_base_article +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bodo_bert_mlm_base_article` is a English model originally trained by alayaran. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bodo_bert_mlm_base_article_en_5.1.1_3.0_1694284578897.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bodo_bert_mlm_base_article_en_5.1.1_3.0_1694284578897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("bodo_bert_mlm_base_article","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("bodo_bert_mlm_base_article", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bodo_bert_mlm_base_article| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|464.2 MB| + +## References + +https://huggingface.co/alayaran/bodo-bert-mlm-base-article \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-covid_trained_bert_en.md b/docs/_posts/ahmedlone127/2023-09-09-covid_trained_bert_en.md new file mode 100644 index 00000000000000..b498c6e8696c74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-covid_trained_bert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English covid_trained_bert BertEmbeddings from timoneda +author: John Snow Labs +name: covid_trained_bert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_trained_bert` is a English model originally trained by timoneda. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_trained_bert_en_5.1.1_3.0_1694260269784.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_trained_bert_en_5.1.1_3.0_1694260269784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("covid_trained_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("covid_trained_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_trained_bert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/timoneda/covid_trained_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-csci544_project_mabel_en.md b/docs/_posts/ahmedlone127/2023-09-09-csci544_project_mabel_en.md new file mode 100644 index 00000000000000..8ae4edc18715c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-csci544_project_mabel_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English csci544_project_mabel BertEmbeddings from adityaanulekh98 +author: John Snow Labs +name: csci544_project_mabel +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`csci544_project_mabel` is a English model originally trained by adityaanulekh98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/csci544_project_mabel_en_5.1.1_3.0_1694265752338.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/csci544_project_mabel_en_5.1.1_3.0_1694265752338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("csci544_project_mabel","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("csci544_project_mabel", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|csci544_project_mabel| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/adityaanulekh98/csci544-project-mabel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-dal_bert_fa.md b/docs/_posts/ahmedlone127/2023-09-09-dal_bert_fa.md new file mode 100644 index 00000000000000..996c3881e5aebf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-dal_bert_fa.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Persian dal_bert BertEmbeddings from sharif-dal +author: John Snow Labs +name: dal_bert +date: 2023-09-09 +tags: [bert, fa, open_source, fill_mask, onnx] +task: Embeddings +language: fa +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dal_bert` is a Persian model originally trained by sharif-dal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dal_bert_fa_5.1.1_3.0_1694284485636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dal_bert_fa_5.1.1_3.0_1694284485636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("dal_bert","fa") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("dal_bert", "fa") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dal_bert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|fa| +|Size:|432.1 MB| + +## References + +https://huggingface.co/sharif-dal/dal-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-dfm_encoder_large_v1_da.md b/docs/_posts/ahmedlone127/2023-09-09-dfm_encoder_large_v1_da.md new file mode 100644 index 00000000000000..49dbf3d48c632c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-dfm_encoder_large_v1_da.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Danish dfm_encoder_large_v1 BertEmbeddings from chcaa +author: John Snow Labs +name: dfm_encoder_large_v1 +date: 2023-09-09 +tags: [bert, da, open_source, fill_mask, onnx] +task: Embeddings +language: da +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dfm_encoder_large_v1` is a Danish model originally trained by chcaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dfm_encoder_large_v1_da_5.1.1_3.0_1694283760247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dfm_encoder_large_v1_da_5.1.1_3.0_1694283760247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("dfm_encoder_large_v1","da") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("dfm_encoder_large_v1", "da") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dfm_encoder_large_v1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|da| +|Size:|1.3 GB| + +## References + +https://huggingface.co/chcaa/dfm-encoder-large-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-dummy_model2_en.md b/docs/_posts/ahmedlone127/2023-09-09-dummy_model2_en.md new file mode 100644 index 00000000000000..a2c46d9328f1cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-dummy_model2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English dummy_model2 BertEmbeddings from vsrinivas +author: John Snow Labs +name: dummy_model2 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model2` is a English model originally trained by vsrinivas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model2_en_5.1.1_3.0_1694259021309.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model2_en_5.1.1_3.0_1694259021309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("dummy_model2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("dummy_model2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model2| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|403.6 MB| + +## References + +https://huggingface.co/vsrinivas/dummy_model2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-finnish_mbertmodel_mberttok_en.md b/docs/_posts/ahmedlone127/2023-09-09-finnish_mbertmodel_mberttok_en.md new file mode 100644 index 00000000000000..351c5b299c51b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-finnish_mbertmodel_mberttok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English finnish_mbertmodel_mberttok BertEmbeddings from hgiyt +author: John Snow Labs +name: finnish_mbertmodel_mberttok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finnish_mbertmodel_mberttok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finnish_mbertmodel_mberttok_en_5.1.1_3.0_1694259583032.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finnish_mbertmodel_mberttok_en_5.1.1_3.0_1694259583032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("finnish_mbertmodel_mberttok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("finnish_mbertmodel_mberttok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finnish_mbertmodel_mberttok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|495.8 MB| + +## References + +https://huggingface.co/hgiyt/fi-mbertmodel-mberttok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-finnish_mbertmodel_monotok_adapter_en.md b/docs/_posts/ahmedlone127/2023-09-09-finnish_mbertmodel_monotok_adapter_en.md new file mode 100644 index 00000000000000..9d3df96780c4c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-finnish_mbertmodel_monotok_adapter_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English finnish_mbertmodel_monotok_adapter BertEmbeddings from hgiyt +author: John Snow Labs +name: finnish_mbertmodel_monotok_adapter +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finnish_mbertmodel_monotok_adapter` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finnish_mbertmodel_monotok_adapter_en_5.1.1_3.0_1694259725340.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finnish_mbertmodel_monotok_adapter_en_5.1.1_3.0_1694259725340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("finnish_mbertmodel_monotok_adapter","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("finnish_mbertmodel_monotok_adapter", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finnish_mbertmodel_monotok_adapter| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|464.9 MB| + +## References + +https://huggingface.co/hgiyt/fi-mbertmodel-monotok-adapter \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-finnish_mbertmodel_monotok_en.md b/docs/_posts/ahmedlone127/2023-09-09-finnish_mbertmodel_monotok_en.md new file mode 100644 index 00000000000000..be93bdb8ed7bae --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-finnish_mbertmodel_monotok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English finnish_mbertmodel_monotok BertEmbeddings from hgiyt +author: John Snow Labs +name: finnish_mbertmodel_monotok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finnish_mbertmodel_monotok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finnish_mbertmodel_monotok_en_5.1.1_3.0_1694259855521.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finnish_mbertmodel_monotok_en_5.1.1_3.0_1694259855521.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("finnish_mbertmodel_monotok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("finnish_mbertmodel_monotok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finnish_mbertmodel_monotok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|464.8 MB| + +## References + +https://huggingface.co/hgiyt/fi-mbertmodel-monotok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-finnish_monomodel_mberttok_en.md b/docs/_posts/ahmedlone127/2023-09-09-finnish_monomodel_mberttok_en.md new file mode 100644 index 00000000000000..9fe1f07f764d9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-finnish_monomodel_mberttok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English finnish_monomodel_mberttok BertEmbeddings from hgiyt +author: John Snow Labs +name: finnish_monomodel_mberttok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finnish_monomodel_mberttok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finnish_monomodel_mberttok_en_5.1.1_3.0_1694260007471.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finnish_monomodel_mberttok_en_5.1.1_3.0_1694260007471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("finnish_monomodel_mberttok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("finnish_monomodel_mberttok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finnish_monomodel_mberttok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|495.0 MB| + +## References + +https://huggingface.co/hgiyt/fi-monomodel-mberttok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-finnish_monomodel_monotok_en.md b/docs/_posts/ahmedlone127/2023-09-09-finnish_monomodel_monotok_en.md new file mode 100644 index 00000000000000..b691d803a28a66 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-finnish_monomodel_monotok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English finnish_monomodel_monotok BertEmbeddings from hgiyt +author: John Snow Labs +name: finnish_monomodel_monotok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finnish_monomodel_monotok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finnish_monomodel_monotok_en_5.1.1_3.0_1694260151850.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finnish_monomodel_monotok_en_5.1.1_3.0_1694260151850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("finnish_monomodel_monotok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("finnish_monomodel_monotok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finnish_monomodel_monotok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|464.3 MB| + +## References + +https://huggingface.co/hgiyt/fi-monomodel-monotok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-german_poetry_bert_en.md b/docs/_posts/ahmedlone127/2023-09-09-german_poetry_bert_en.md new file mode 100644 index 00000000000000..86e9ae2018fe3d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-german_poetry_bert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English german_poetry_bert BertEmbeddings from Anjoe +author: John Snow Labs +name: german_poetry_bert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_poetry_bert` is a English model originally trained by Anjoe. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_poetry_bert_en_5.1.1_3.0_1694284344164.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_poetry_bert_en_5.1.1_3.0_1694284344164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("german_poetry_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("german_poetry_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|german_poetry_bert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|409.9 MB| + +## References + +https://huggingface.co/Anjoe/german-poetry-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-guidebias_bert_base_uncased_gender_en.md b/docs/_posts/ahmedlone127/2023-09-09-guidebias_bert_base_uncased_gender_en.md new file mode 100644 index 00000000000000..eb4ca7e3a3c3d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-guidebias_bert_base_uncased_gender_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English guidebias_bert_base_uncased_gender BertEmbeddings from squiduu +author: John Snow Labs +name: guidebias_bert_base_uncased_gender +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`guidebias_bert_base_uncased_gender` is a English model originally trained by squiduu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/guidebias_bert_base_uncased_gender_en_5.1.1_3.0_1694283230300.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/guidebias_bert_base_uncased_gender_en_5.1.1_3.0_1694283230300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("guidebias_bert_base_uncased_gender","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("guidebias_bert_base_uncased_gender", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|guidebias_bert_base_uncased_gender| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/squiduu/guidebias-bert-base-uncased-gender \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-gujbert_senti_a_en.md b/docs/_posts/ahmedlone127/2023-09-09-gujbert_senti_a_en.md new file mode 100644 index 00000000000000..58864a3b814cd5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-gujbert_senti_a_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English gujbert_senti_a BertEmbeddings from kvaditya +author: John Snow Labs +name: gujbert_senti_a +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gujbert_senti_a` is a English model originally trained by kvaditya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gujbert_senti_a_en_5.1.1_3.0_1694265938762.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gujbert_senti_a_en_5.1.1_3.0_1694265938762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("gujbert_senti_a","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("gujbert_senti_a", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gujbert_senti_a| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|890.4 MB| + +## References + +https://huggingface.co/kvaditya/gujbert-senti-a \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-gww_en.md b/docs/_posts/ahmedlone127/2023-09-09-gww_en.md new file mode 100644 index 00000000000000..cb117e2e539933 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-gww_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English gww BertEmbeddings from dunlp +author: John Snow Labs +name: gww +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gww` is a English model originally trained by dunlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gww_en_5.1.1_3.0_1694284784080.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gww_en_5.1.1_3.0_1694284784080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("gww","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("gww", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gww| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/dunlp/GWW \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-hubert_base_cc_finetuned_forum_en.md b/docs/_posts/ahmedlone127/2023-09-09-hubert_base_cc_finetuned_forum_en.md new file mode 100644 index 00000000000000..42ed9d84a626f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-hubert_base_cc_finetuned_forum_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English hubert_base_cc_finetuned_forum BertEmbeddings from papsebestyen +author: John Snow Labs +name: hubert_base_cc_finetuned_forum +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_base_cc_finetuned_forum` is a English model originally trained by papsebestyen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_base_cc_finetuned_forum_en_5.1.1_3.0_1694266159584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_base_cc_finetuned_forum_en_5.1.1_3.0_1694266159584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("hubert_base_cc_finetuned_forum","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("hubert_base_cc_finetuned_forum", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_base_cc_finetuned_forum| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|412.4 MB| + +## References + +https://huggingface.co/papsebestyen/hubert-base-cc-finetuned-forum \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-indobert_base_uncased_id.md b/docs/_posts/ahmedlone127/2023-09-09-indobert_base_uncased_id.md new file mode 100644 index 00000000000000..2c85ca6c717784 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-indobert_base_uncased_id.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Indonesian indobert_base_uncased BertEmbeddings from indolem +author: John Snow Labs +name: indobert_base_uncased +date: 2023-09-09 +tags: [bert, id, open_source, fill_mask, onnx] +task: Embeddings +language: id +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_base_uncased` is a Indonesian model originally trained by indolem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_base_uncased_id_5.1.1_3.0_1694267045811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_base_uncased_id_5.1.1_3.0_1694267045811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("indobert_base_uncased","id") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("indobert_base_uncased", "id") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobert_base_uncased| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|id| +|Size:|411.7 MB| + +## References + +https://huggingface.co/indolem/indobert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-indobertweet_base_uncased_id.md b/docs/_posts/ahmedlone127/2023-09-09-indobertweet_base_uncased_id.md new file mode 100644 index 00000000000000..0b5e8b7cbaa93b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-indobertweet_base_uncased_id.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Indonesian indobertweet_base_uncased BertEmbeddings from indolem +author: John Snow Labs +name: indobertweet_base_uncased +date: 2023-09-09 +tags: [bert, id, open_source, fill_mask, onnx] +task: Embeddings +language: id +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobertweet_base_uncased` is a Indonesian model originally trained by indolem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobertweet_base_uncased_id_5.1.1_3.0_1694267225929.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobertweet_base_uncased_id_5.1.1_3.0_1694267225929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("indobertweet_base_uncased","id") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("indobertweet_base_uncased", "id") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobertweet_base_uncased| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|id| +|Size:|411.8 MB| + +## References + +https://huggingface.co/indolem/indobertweet-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-indojave_codemixed_indobertweet_base_id.md b/docs/_posts/ahmedlone127/2023-09-09-indojave_codemixed_indobertweet_base_id.md new file mode 100644 index 00000000000000..90d3b0e0b2d697 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-indojave_codemixed_indobertweet_base_id.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Indonesian indojave_codemixed_indobertweet_base BertEmbeddings from fathan +author: John Snow Labs +name: indojave_codemixed_indobertweet_base +date: 2023-09-09 +tags: [bert, id, open_source, fill_mask, onnx] +task: Embeddings +language: id +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indojave_codemixed_indobertweet_base` is a Indonesian model originally trained by fathan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indojave_codemixed_indobertweet_base_id_5.1.1_3.0_1694283480900.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indojave_codemixed_indobertweet_base_id_5.1.1_3.0_1694283480900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("indojave_codemixed_indobertweet_base","id") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("indojave_codemixed_indobertweet_base", "id") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indojave_codemixed_indobertweet_base| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|id| +|Size:|411.8 MB| + +## References + +https://huggingface.co/fathan/indojave-codemixed-indobertweet-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-indonesian_mbertmodel_mberttok_en.md b/docs/_posts/ahmedlone127/2023-09-09-indonesian_mbertmodel_mberttok_en.md new file mode 100644 index 00000000000000..a58d7856fa417f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-indonesian_mbertmodel_mberttok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English indonesian_mbertmodel_mberttok BertEmbeddings from hgiyt +author: John Snow Labs +name: indonesian_mbertmodel_mberttok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_mbertmodel_mberttok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_mbertmodel_mberttok_en_5.1.1_3.0_1694260328909.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_mbertmodel_mberttok_en_5.1.1_3.0_1694260328909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("indonesian_mbertmodel_mberttok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("indonesian_mbertmodel_mberttok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indonesian_mbertmodel_mberttok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|530.3 MB| + +## References + +https://huggingface.co/hgiyt/id-mbertmodel-mberttok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-indonesian_mbertmodel_monotok_adapter_en.md b/docs/_posts/ahmedlone127/2023-09-09-indonesian_mbertmodel_monotok_adapter_en.md new file mode 100644 index 00000000000000..14486aab74aafb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-indonesian_mbertmodel_monotok_adapter_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English indonesian_mbertmodel_monotok_adapter BertEmbeddings from hgiyt +author: John Snow Labs +name: indonesian_mbertmodel_monotok_adapter +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_mbertmodel_monotok_adapter` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_mbertmodel_monotok_adapter_en_5.1.1_3.0_1694260454540.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_mbertmodel_monotok_adapter_en_5.1.1_3.0_1694260454540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("indonesian_mbertmodel_monotok_adapter","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("indonesian_mbertmodel_monotok_adapter", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indonesian_mbertmodel_monotok_adapter| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.3 MB| + +## References + +https://huggingface.co/hgiyt/id-mbertmodel-monotok-adapter \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-indonesian_mbertmodel_monotok_en.md b/docs/_posts/ahmedlone127/2023-09-09-indonesian_mbertmodel_monotok_en.md new file mode 100644 index 00000000000000..dc4930da8ba45e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-indonesian_mbertmodel_monotok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English indonesian_mbertmodel_monotok BertEmbeddings from hgiyt +author: John Snow Labs +name: indonesian_mbertmodel_monotok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_mbertmodel_monotok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_mbertmodel_monotok_en_5.1.1_3.0_1694260586722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_mbertmodel_monotok_en_5.1.1_3.0_1694260586722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("indonesian_mbertmodel_monotok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("indonesian_mbertmodel_monotok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indonesian_mbertmodel_monotok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.3 MB| + +## References + +https://huggingface.co/hgiyt/id-mbertmodel-monotok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-indonesian_monomodel_mberttok_en.md b/docs/_posts/ahmedlone127/2023-09-09-indonesian_monomodel_mberttok_en.md new file mode 100644 index 00000000000000..04218e1af7b8b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-indonesian_monomodel_mberttok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English indonesian_monomodel_mberttok BertEmbeddings from hgiyt +author: John Snow Labs +name: indonesian_monomodel_mberttok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_monomodel_mberttok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_monomodel_mberttok_en_5.1.1_3.0_1694260741116.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_monomodel_mberttok_en_5.1.1_3.0_1694260741116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("indonesian_monomodel_mberttok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("indonesian_monomodel_mberttok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indonesian_monomodel_mberttok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|529.3 MB| + +## References + +https://huggingface.co/hgiyt/id-monomodel-mberttok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-indonesian_monomodel_monotok_en.md b/docs/_posts/ahmedlone127/2023-09-09-indonesian_monomodel_monotok_en.md new file mode 100644 index 00000000000000..63f5f1a1a70b5d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-indonesian_monomodel_monotok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English indonesian_monomodel_monotok BertEmbeddings from hgiyt +author: John Snow Labs +name: indonesian_monomodel_monotok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_monomodel_monotok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_monomodel_monotok_en_5.1.1_3.0_1694260879482.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_monomodel_monotok_en_5.1.1_3.0_1694260879482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("indonesian_monomodel_monotok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("indonesian_monomodel_monotok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indonesian_monomodel_monotok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.0 MB| + +## References + +https://huggingface.co/hgiyt/id-monomodel-monotok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-inlegalbert_cbp_lkg_triples_finetuned_en.md b/docs/_posts/ahmedlone127/2023-09-09-inlegalbert_cbp_lkg_triples_finetuned_en.md new file mode 100644 index 00000000000000..003e102784eb39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-inlegalbert_cbp_lkg_triples_finetuned_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English inlegalbert_cbp_lkg_triples_finetuned BertEmbeddings from kinshuk-h +author: John Snow Labs +name: inlegalbert_cbp_lkg_triples_finetuned +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`inlegalbert_cbp_lkg_triples_finetuned` is a English model originally trained by kinshuk-h. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/inlegalbert_cbp_lkg_triples_finetuned_en_5.1.1_3.0_1694266522167.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/inlegalbert_cbp_lkg_triples_finetuned_en_5.1.1_3.0_1694266522167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("inlegalbert_cbp_lkg_triples_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("inlegalbert_cbp_lkg_triples_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|inlegalbert_cbp_lkg_triples_finetuned| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/kinshuk-h/InLegalBERT-cbp-lkg-triples-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-javabert_en.md b/docs/_posts/ahmedlone127/2023-09-09-javabert_en.md new file mode 100644 index 00000000000000..c1b144b9f1b5e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-javabert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English javabert BertEmbeddings from CAUKiel +author: John Snow Labs +name: javabert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`javabert` is a English model originally trained by CAUKiel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/javabert_en_5.1.1_3.0_1694266219357.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/javabert_en_5.1.1_3.0_1694266219357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("javabert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("javabert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|javabert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/CAUKiel/JavaBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-javabert_uncased_en.md b/docs/_posts/ahmedlone127/2023-09-09-javabert_uncased_en.md new file mode 100644 index 00000000000000..1cdbfb654cef4f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-javabert_uncased_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English javabert_uncased BertEmbeddings from CAUKiel +author: John Snow Labs +name: javabert_uncased +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`javabert_uncased` is a English model originally trained by CAUKiel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/javabert_uncased_en_5.1.1_3.0_1694266075550.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/javabert_uncased_en_5.1.1_3.0_1694266075550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("javabert_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("javabert_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|javabert_uncased| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/CAUKiel/JavaBERT-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-jobbert_org_add_words_trial_26_12_2022_en.md b/docs/_posts/ahmedlone127/2023-09-09-jobbert_org_add_words_trial_26_12_2022_en.md new file mode 100644 index 00000000000000..1d4f21d35bdd44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-jobbert_org_add_words_trial_26_12_2022_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English jobbert_org_add_words_trial_26_12_2022 BertEmbeddings from EslamAhmed +author: John Snow Labs +name: jobbert_org_add_words_trial_26_12_2022 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jobbert_org_add_words_trial_26_12_2022` is a English model originally trained by EslamAhmed. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jobbert_org_add_words_trial_26_12_2022_en_5.1.1_3.0_1694278226503.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jobbert_org_add_words_trial_26_12_2022_en_5.1.1_3.0_1694278226503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("jobbert_org_add_words_trial_26_12_2022","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("jobbert_org_add_words_trial_26_12_2022", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|jobbert_org_add_words_trial_26_12_2022| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|447.4 MB| + +## References + +https://huggingface.co/EslamAhmed/JOBBERT_org_add_words_trial_26-12-2022 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-jobbert_org_add_words_v2_trial_26_12_2022_en.md b/docs/_posts/ahmedlone127/2023-09-09-jobbert_org_add_words_v2_trial_26_12_2022_en.md new file mode 100644 index 00000000000000..7f42c389668eaa --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-jobbert_org_add_words_v2_trial_26_12_2022_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English jobbert_org_add_words_v2_trial_26_12_2022 BertEmbeddings from EslamAhmed +author: John Snow Labs +name: jobbert_org_add_words_v2_trial_26_12_2022 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jobbert_org_add_words_v2_trial_26_12_2022` is a English model originally trained by EslamAhmed. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jobbert_org_add_words_v2_trial_26_12_2022_en_5.1.1_3.0_1694278342003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jobbert_org_add_words_v2_trial_26_12_2022_en_5.1.1_3.0_1694278342003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("jobbert_org_add_words_v2_trial_26_12_2022","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("jobbert_org_add_words_v2_trial_26_12_2022", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|jobbert_org_add_words_v2_trial_26_12_2022| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|447.4 MB| + +## References + +https://huggingface.co/EslamAhmed/JOBBERT_org_add_words_v2_trial_26-12-2022 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-jobbert_test_org_trial_26_12_2022_en.md b/docs/_posts/ahmedlone127/2023-09-09-jobbert_test_org_trial_26_12_2022_en.md new file mode 100644 index 00000000000000..2c66afe1adbbbe --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-jobbert_test_org_trial_26_12_2022_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English jobbert_test_org_trial_26_12_2022 BertEmbeddings from EslamAhmed +author: John Snow Labs +name: jobbert_test_org_trial_26_12_2022 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jobbert_test_org_trial_26_12_2022` is a English model originally trained by EslamAhmed. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jobbert_test_org_trial_26_12_2022_en_5.1.1_3.0_1694267094649.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jobbert_test_org_trial_26_12_2022_en_5.1.1_3.0_1694267094649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("jobbert_test_org_trial_26_12_2022","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("jobbert_test_org_trial_26_12_2022", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|jobbert_test_org_trial_26_12_2022| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|402.1 MB| + +## References + +https://huggingface.co/EslamAhmed/JOBBERT_test_org_trial_26-12-2022 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-jzmodel01_en.md b/docs/_posts/ahmedlone127/2023-09-09-jzmodel01_en.md new file mode 100644 index 00000000000000..b89266c640697d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-jzmodel01_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English jzmodel01 BertEmbeddings from jinzhan +author: John Snow Labs +name: jzmodel01 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jzmodel01` is a English model originally trained by jinzhan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jzmodel01_en_5.1.1_3.0_1694283002753.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jzmodel01_en_5.1.1_3.0_1694283002753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("jzmodel01","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("jzmodel01", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|jzmodel01| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/jinzhan/jzmodel01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kaz_legal_bert_5_en.md b/docs/_posts/ahmedlone127/2023-09-09-kaz_legal_bert_5_en.md new file mode 100644 index 00000000000000..f749093710f761 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kaz_legal_bert_5_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kaz_legal_bert_5 BertEmbeddings from kaisar-barlybay-sse +author: John Snow Labs +name: kaz_legal_bert_5 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kaz_legal_bert_5` is a English model originally trained by kaisar-barlybay-sse. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kaz_legal_bert_5_en_5.1.1_3.0_1694279378634.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kaz_legal_bert_5_en_5.1.1_3.0_1694279378634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kaz_legal_bert_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kaz_legal_bert_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kaz_legal_bert_5| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.0 MB| + +## References + +https://huggingface.co/kaisar-barlybay-sse/kaz_legal_bert_5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kaz_legal_bert_en.md b/docs/_posts/ahmedlone127/2023-09-09-kaz_legal_bert_en.md new file mode 100644 index 00000000000000..ddd445cde44b74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kaz_legal_bert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kaz_legal_bert BertEmbeddings from kaisar-barlybay-sse +author: John Snow Labs +name: kaz_legal_bert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kaz_legal_bert` is a English model originally trained by kaisar-barlybay-sse. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kaz_legal_bert_en_5.1.1_3.0_1694278999873.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kaz_legal_bert_en_5.1.1_3.0_1694278999873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kaz_legal_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kaz_legal_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kaz_legal_bert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.0 MB| + +## References + +https://huggingface.co/kaisar-barlybay-sse/kaz_legal_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kbert_base_esg_e10_en.md b/docs/_posts/ahmedlone127/2023-09-09-kbert_base_esg_e10_en.md new file mode 100644 index 00000000000000..e8786b2c03fb60 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kbert_base_esg_e10_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kbert_base_esg_e10 BertEmbeddings from jinbbong +author: John Snow Labs +name: kbert_base_esg_e10 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kbert_base_esg_e10` is a English model originally trained by jinbbong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kbert_base_esg_e10_en_5.1.1_3.0_1694280021278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kbert_base_esg_e10_en_5.1.1_3.0_1694280021278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kbert_base_esg_e10","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kbert_base_esg_e10", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kbert_base_esg_e10| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|441.2 MB| + +## References + +https://huggingface.co/jinbbong/kbert_base_esg_e10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kbert_base_esg_e3_en.md b/docs/_posts/ahmedlone127/2023-09-09-kbert_base_esg_e3_en.md new file mode 100644 index 00000000000000..842df31a86d4af --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kbert_base_esg_e3_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kbert_base_esg_e3 BertEmbeddings from jinbbong +author: John Snow Labs +name: kbert_base_esg_e3 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kbert_base_esg_e3` is a English model originally trained by jinbbong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kbert_base_esg_e3_en_5.1.1_3.0_1694280184375.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kbert_base_esg_e3_en_5.1.1_3.0_1694280184375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kbert_base_esg_e3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kbert_base_esg_e3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kbert_base_esg_e3| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|441.2 MB| + +## References + +https://huggingface.co/jinbbong/kbert_base_esg_e3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kbert_base_esg_e5_en.md b/docs/_posts/ahmedlone127/2023-09-09-kbert_base_esg_e5_en.md new file mode 100644 index 00000000000000..7ef1ad8d43fe97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kbert_base_esg_e5_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kbert_base_esg_e5 BertEmbeddings from jinbbong +author: John Snow Labs +name: kbert_base_esg_e5 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kbert_base_esg_e5` is a English model originally trained by jinbbong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kbert_base_esg_e5_en_5.1.1_3.0_1694280334055.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kbert_base_esg_e5_en_5.1.1_3.0_1694280334055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kbert_base_esg_e5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kbert_base_esg_e5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kbert_base_esg_e5| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|441.2 MB| + +## References + +https://huggingface.co/jinbbong/kbert_base_esg_e5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kinyabert_large_en.md b/docs/_posts/ahmedlone127/2023-09-09-kinyabert_large_en.md new file mode 100644 index 00000000000000..f4c612a45d1cd8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kinyabert_large_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kinyabert_large BertEmbeddings from jean-paul +author: John Snow Labs +name: kinyabert_large +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kinyabert_large` is a English model originally trained by jean-paul. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kinyabert_large_en_5.1.1_3.0_1694279233724.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kinyabert_large_en_5.1.1_3.0_1694279233724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kinyabert_large","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kinyabert_large", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kinyabert_large| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/jean-paul/KinyaBERT-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kinyabert_small_en.md b/docs/_posts/ahmedlone127/2023-09-09-kinyabert_small_en.md new file mode 100644 index 00000000000000..8b3fdc3da7be2e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kinyabert_small_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kinyabert_small BertEmbeddings from jean-paul +author: John Snow Labs +name: kinyabert_small +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kinyabert_small` is a English model originally trained by jean-paul. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kinyabert_small_en_5.1.1_3.0_1694279349541.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kinyabert_small_en_5.1.1_3.0_1694279349541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kinyabert_small","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kinyabert_small", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kinyabert_small| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|247.4 MB| + +## References + +https://huggingface.co/jean-paul/KinyaBERT-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-knowbias_bert_base_uncased_gender_en.md b/docs/_posts/ahmedlone127/2023-09-09-knowbias_bert_base_uncased_gender_en.md new file mode 100644 index 00000000000000..394c2c5d2ab70b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-knowbias_bert_base_uncased_gender_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English knowbias_bert_base_uncased_gender BertEmbeddings from squiduu +author: John Snow Labs +name: knowbias_bert_base_uncased_gender +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`knowbias_bert_base_uncased_gender` is a English model originally trained by squiduu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/knowbias_bert_base_uncased_gender_en_5.1.1_3.0_1694279779070.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/knowbias_bert_base_uncased_gender_en_5.1.1_3.0_1694279779070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("knowbias_bert_base_uncased_gender","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("knowbias_bert_base_uncased_gender", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|knowbias_bert_base_uncased_gender| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/squiduu/knowbias-bert-base-uncased-gender \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-korean_mbertmodel_mberttok_en.md b/docs/_posts/ahmedlone127/2023-09-09-korean_mbertmodel_mberttok_en.md new file mode 100644 index 00000000000000..f94be219287cf0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-korean_mbertmodel_mberttok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English korean_mbertmodel_mberttok BertEmbeddings from hgiyt +author: John Snow Labs +name: korean_mbertmodel_mberttok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`korean_mbertmodel_mberttok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/korean_mbertmodel_mberttok_en_5.1.1_3.0_1694261027566.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/korean_mbertmodel_mberttok_en_5.1.1_3.0_1694261027566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("korean_mbertmodel_mberttok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("korean_mbertmodel_mberttok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|korean_mbertmodel_mberttok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|511.4 MB| + +## References + +https://huggingface.co/hgiyt/ko-mbertmodel-mberttok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-korean_monomodel_mberttok_en.md b/docs/_posts/ahmedlone127/2023-09-09-korean_monomodel_mberttok_en.md new file mode 100644 index 00000000000000..d7698f059b151e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-korean_monomodel_mberttok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English korean_monomodel_mberttok BertEmbeddings from hgiyt +author: John Snow Labs +name: korean_monomodel_mberttok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`korean_monomodel_mberttok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/korean_monomodel_mberttok_en_5.1.1_3.0_1694265026447.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/korean_monomodel_mberttok_en_5.1.1_3.0_1694265026447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("korean_monomodel_mberttok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("korean_monomodel_mberttok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|korean_monomodel_mberttok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|510.1 MB| + +## References + +https://huggingface.co/hgiyt/ko-monomodel-mberttok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_10000_0.000006_en.md b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_10000_0.000006_en.md new file mode 100644 index 00000000000000..8befc8261b3a36 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_10000_0.000006_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kw_pubmed_10000_0.000006 BertEmbeddings from enoriega +author: John Snow Labs +name: kw_pubmed_10000_0.000006 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kw_pubmed_10000_0.000006` is a English model originally trained by enoriega. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kw_pubmed_10000_0.000006_en_5.1.1_3.0_1694259822636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kw_pubmed_10000_0.000006_en_5.1.1_3.0_1694259822636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kw_pubmed_10000_0.000006","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kw_pubmed_10000_0.000006", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kw_pubmed_10000_0.000006| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/enoriega/kw_pubmed_10000_0.000006 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_10000_0.00006_en.md b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_10000_0.00006_en.md new file mode 100644 index 00000000000000..af8c39513cdd63 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_10000_0.00006_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kw_pubmed_10000_0.00006 BertEmbeddings from enoriega +author: John Snow Labs +name: kw_pubmed_10000_0.00006 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kw_pubmed_10000_0.00006` is a English model originally trained by enoriega. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kw_pubmed_10000_0.00006_en_5.1.1_3.0_1694259256891.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kw_pubmed_10000_0.00006_en_5.1.1_3.0_1694259256891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kw_pubmed_10000_0.00006","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kw_pubmed_10000_0.00006", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kw_pubmed_10000_0.00006| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/enoriega/kw_pubmed_10000_0.00006 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_10000_0.0003_en.md b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_10000_0.0003_en.md new file mode 100644 index 00000000000000..4482261945e5ea --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_10000_0.0003_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kw_pubmed_10000_0.0003 BertEmbeddings from enoriega +author: John Snow Labs +name: kw_pubmed_10000_0.0003 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kw_pubmed_10000_0.0003` is a English model originally trained by enoriega. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kw_pubmed_10000_0.0003_en_5.1.1_3.0_1694259557823.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kw_pubmed_10000_0.0003_en_5.1.1_3.0_1694259557823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kw_pubmed_10000_0.0003","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kw_pubmed_10000_0.0003", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kw_pubmed_10000_0.0003| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/enoriega/kw_pubmed_10000_0.0003 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_5000_0.000006_en.md b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_5000_0.000006_en.md new file mode 100644 index 00000000000000..f8b3fa206ed2d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_5000_0.000006_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kw_pubmed_5000_0.000006 BertEmbeddings from enoriega +author: John Snow Labs +name: kw_pubmed_5000_0.000006 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kw_pubmed_5000_0.000006` is a English model originally trained by enoriega. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kw_pubmed_5000_0.000006_en_5.1.1_3.0_1694259689852.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kw_pubmed_5000_0.000006_en_5.1.1_3.0_1694259689852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kw_pubmed_5000_0.000006","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kw_pubmed_5000_0.000006", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kw_pubmed_5000_0.000006| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/enoriega/kw_pubmed_5000_0.000006 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_5000_0.00006_en.md b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_5000_0.00006_en.md new file mode 100644 index 00000000000000..293575a5a53b4d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_5000_0.00006_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kw_pubmed_5000_0.00006 BertEmbeddings from enoriega +author: John Snow Labs +name: kw_pubmed_5000_0.00006 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kw_pubmed_5000_0.00006` is a English model originally trained by enoriega. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kw_pubmed_5000_0.00006_en_5.1.1_3.0_1694259408552.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kw_pubmed_5000_0.00006_en_5.1.1_3.0_1694259408552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kw_pubmed_5000_0.00006","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kw_pubmed_5000_0.00006", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kw_pubmed_5000_0.00006| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/enoriega/kw_pubmed_5000_0.00006 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_5000_0.0003_en.md b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_5000_0.0003_en.md new file mode 100644 index 00000000000000..992f6205d99d41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-kw_pubmed_5000_0.0003_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English kw_pubmed_5000_0.0003 BertEmbeddings from enoriega +author: John Snow Labs +name: kw_pubmed_5000_0.0003 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kw_pubmed_5000_0.0003` is a English model originally trained by enoriega. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kw_pubmed_5000_0.0003_en_5.1.1_3.0_1694259116149.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kw_pubmed_5000_0.0003_en_5.1.1_3.0_1694259116149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("kw_pubmed_5000_0.0003","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("kw_pubmed_5000_0.0003", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kw_pubmed_5000_0.0003| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/enoriega/kw_pubmed_5000_0.0003 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-legal_bert_base_uncased_finetuned_ledgarscotus7_en.md b/docs/_posts/ahmedlone127/2023-09-09-legal_bert_base_uncased_finetuned_ledgarscotus7_en.md new file mode 100644 index 00000000000000..8fb546e076f123 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-legal_bert_base_uncased_finetuned_ledgarscotus7_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English legal_bert_base_uncased_finetuned_ledgarscotus7 BertEmbeddings from hatemestinbejaia +author: John Snow Labs +name: legal_bert_base_uncased_finetuned_ledgarscotus7 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_bert_base_uncased_finetuned_ledgarscotus7` is a English model originally trained by hatemestinbejaia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_bert_base_uncased_finetuned_ledgarscotus7_en_5.1.1_3.0_1694278582359.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_bert_base_uncased_finetuned_ledgarscotus7_en_5.1.1_3.0_1694278582359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("legal_bert_base_uncased_finetuned_ledgarscotus7","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("legal_bert_base_uncased_finetuned_ledgarscotus7", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_bert_base_uncased_finetuned_ledgarscotus7| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/hatemestinbejaia/legal-bert-base-uncased-finetuned-ledgarscotus7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-lsg16k_italian_legal_bert_it.md b/docs/_posts/ahmedlone127/2023-09-09-lsg16k_italian_legal_bert_it.md new file mode 100644 index 00000000000000..f3256238134713 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-lsg16k_italian_legal_bert_it.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Italian lsg16k_italian_legal_bert BertEmbeddings from dlicari +author: John Snow Labs +name: lsg16k_italian_legal_bert +date: 2023-09-09 +tags: [bert, it, open_source, fill_mask, onnx] +task: Embeddings +language: it +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lsg16k_italian_legal_bert` is a Italian model originally trained by dlicari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lsg16k_italian_legal_bert_it_5.1.1_3.0_1694259755707.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lsg16k_italian_legal_bert_it_5.1.1_3.0_1694259755707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("lsg16k_italian_legal_bert","it") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("lsg16k_italian_legal_bert", "it") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lsg16k_italian_legal_bert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|it| +|Size:|454.6 MB| + +## References + +https://huggingface.co/dlicari/lsg16k-Italian-Legal-BERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-materialsbert_en.md b/docs/_posts/ahmedlone127/2023-09-09-materialsbert_en.md new file mode 100644 index 00000000000000..1c05d73f30f44c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-materialsbert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English materialsbert BertEmbeddings from pranav-s +author: John Snow Labs +name: materialsbert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`materialsbert` is a English model originally trained by pranav-s. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/materialsbert_en_5.1.1_3.0_1694283977428.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/materialsbert_en_5.1.1_3.0_1694283977428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("materialsbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("materialsbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|materialsbert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.9 MB| + +## References + +https://huggingface.co/pranav-s/MaterialsBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-medbert_breastcancer_en.md b/docs/_posts/ahmedlone127/2023-09-09-medbert_breastcancer_en.md new file mode 100644 index 00000000000000..018573d6cb654a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-medbert_breastcancer_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English medbert_breastcancer BertEmbeddings from Gaborandi +author: John Snow Labs +name: medbert_breastcancer +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medbert_breastcancer` is a English model originally trained by Gaborandi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medbert_breastcancer_en_5.1.1_3.0_1694279810961.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medbert_breastcancer_en_5.1.1_3.0_1694279810961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("medbert_breastcancer","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("medbert_breastcancer", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|medbert_breastcancer| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|402.7 MB| + +## References + +https://huggingface.co/Gaborandi/MedBERT-breastcancer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-medium_mlm_imdb_en.md b/docs/_posts/ahmedlone127/2023-09-09-medium_mlm_imdb_en.md new file mode 100644 index 00000000000000..6c47bcf27c1088 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-medium_mlm_imdb_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English medium_mlm_imdb BertEmbeddings from muhtasham +author: John Snow Labs +name: medium_mlm_imdb +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medium_mlm_imdb` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medium_mlm_imdb_en_5.1.1_3.0_1694258626582.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medium_mlm_imdb_en_5.1.1_3.0_1694258626582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("medium_mlm_imdb","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("medium_mlm_imdb", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|medium_mlm_imdb| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|154.2 MB| + +## References + +https://huggingface.co/muhtasham/medium-mlm-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-metaphor_finetuned_bert_5epochs_en.md b/docs/_posts/ahmedlone127/2023-09-09-metaphor_finetuned_bert_5epochs_en.md new file mode 100644 index 00000000000000..9ed52e130aa7a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-metaphor_finetuned_bert_5epochs_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English metaphor_finetuned_bert_5epochs BertEmbeddings from kangela +author: John Snow Labs +name: metaphor_finetuned_bert_5epochs +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`metaphor_finetuned_bert_5epochs` is a English model originally trained by kangela. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/metaphor_finetuned_bert_5epochs_en_5.1.1_3.0_1694283470378.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/metaphor_finetuned_bert_5epochs_en_5.1.1_3.0_1694283470378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("metaphor_finetuned_bert_5epochs","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("metaphor_finetuned_bert_5epochs", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|metaphor_finetuned_bert_5epochs| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/kangela/Metaphor-FineTuned-BERT-5Epochs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-mlm_20230427_indobertlarge_001_en.md b/docs/_posts/ahmedlone127/2023-09-09-mlm_20230427_indobertlarge_001_en.md new file mode 100644 index 00000000000000..444e875589cfe7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-mlm_20230427_indobertlarge_001_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mlm_20230427_indobertlarge_001 BertEmbeddings from intanm +author: John Snow Labs +name: mlm_20230427_indobertlarge_001 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_20230427_indobertlarge_001` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_20230427_indobertlarge_001_en_5.1.1_3.0_1694280023038.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_20230427_indobertlarge_001_en_5.1.1_3.0_1694280023038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("mlm_20230427_indobertlarge_001","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("mlm_20230427_indobertlarge_001", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mlm_20230427_indobertlarge_001| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/intanm/mlm-20230427-IndoBERTLarge-001 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-mlm_20230427_mbert_001_en.md b/docs/_posts/ahmedlone127/2023-09-09-mlm_20230427_mbert_001_en.md new file mode 100644 index 00000000000000..4d75de27e5dceb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-mlm_20230427_mbert_001_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mlm_20230427_mbert_001 BertEmbeddings from intanm +author: John Snow Labs +name: mlm_20230427_mbert_001 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_20230427_mbert_001` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_20230427_mbert_001_en_5.1.1_3.0_1694279570434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_20230427_mbert_001_en_5.1.1_3.0_1694279570434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("mlm_20230427_mbert_001","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("mlm_20230427_mbert_001", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mlm_20230427_mbert_001| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|665.0 MB| + +## References + +https://huggingface.co/intanm/mlm-20230427-mBERT-001 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-mlm_20230428_indobert_base_p2_001_en.md b/docs/_posts/ahmedlone127/2023-09-09-mlm_20230428_indobert_base_p2_001_en.md new file mode 100644 index 00000000000000..02519bca0d489e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-mlm_20230428_indobert_base_p2_001_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mlm_20230428_indobert_base_p2_001 BertEmbeddings from intanm +author: John Snow Labs +name: mlm_20230428_indobert_base_p2_001 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_20230428_indobert_base_p2_001` is a English model originally trained by intanm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_20230428_indobert_base_p2_001_en_5.1.1_3.0_1694283914581.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_20230428_indobert_base_p2_001_en_5.1.1_3.0_1694283914581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("mlm_20230428_indobert_base_p2_001","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("mlm_20230428_indobert_base_p2_001", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mlm_20230428_indobert_base_p2_001| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|464.2 MB| + +## References + +https://huggingface.co/intanm/mlm-20230428-indobert-base-p2-001 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-mtl_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2023-09-09-mtl_bert_base_uncased_en.md new file mode 100644 index 00000000000000..4d77dabecf3c93 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-mtl_bert_base_uncased_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mtl_bert_base_uncased BertEmbeddings from jgammack +author: John Snow Labs +name: mtl_bert_base_uncased +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mtl_bert_base_uncased` is a English model originally trained by jgammack. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mtl_bert_base_uncased_en_5.1.1_3.0_1694279621938.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mtl_bert_base_uncased_en_5.1.1_3.0_1694279621938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("mtl_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("mtl_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mtl_bert_base_uncased| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/jgammack/MTL-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-mtl_bert_base_uncased_ww_en.md b/docs/_posts/ahmedlone127/2023-09-09-mtl_bert_base_uncased_ww_en.md new file mode 100644 index 00000000000000..323231ff9ef067 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-mtl_bert_base_uncased_ww_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mtl_bert_base_uncased_ww BertEmbeddings from jgammack +author: John Snow Labs +name: mtl_bert_base_uncased_ww +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mtl_bert_base_uncased_ww` is a English model originally trained by jgammack. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mtl_bert_base_uncased_ww_en_5.1.1_3.0_1694279504952.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mtl_bert_base_uncased_ww_en_5.1.1_3.0_1694279504952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("mtl_bert_base_uncased_ww","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("mtl_bert_base_uncased_ww", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mtl_bert_base_uncased_ww| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/jgammack/MTL-bert-base-uncased-ww \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-mymodel04_illvmi_en.md b/docs/_posts/ahmedlone127/2023-09-09-mymodel04_illvmi_en.md new file mode 100644 index 00000000000000..dc704c8fa320a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-mymodel04_illvmi_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English mymodel04_illvmi BertEmbeddings from illvmi +author: John Snow Labs +name: mymodel04_illvmi +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mymodel04_illvmi` is a English model originally trained by illvmi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mymodel04_illvmi_en_5.1.1_3.0_1694266908899.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mymodel04_illvmi_en_5.1.1_3.0_1694266908899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("mymodel04_illvmi","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("mymodel04_illvmi", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mymodel04_illvmi| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/illvmi/mymodel04 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-nepali_bert_npvec1_en.md b/docs/_posts/ahmedlone127/2023-09-09-nepali_bert_npvec1_en.md new file mode 100644 index 00000000000000..effdf89c0a764f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-nepali_bert_npvec1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English nepali_bert_npvec1 BertEmbeddings from nowalab +author: John Snow Labs +name: nepali_bert_npvec1 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepali_bert_npvec1` is a English model originally trained by nowalab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepali_bert_npvec1_en_5.1.1_3.0_1694282954336.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepali_bert_npvec1_en_5.1.1_3.0_1694282954336.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("nepali_bert_npvec1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("nepali_bert_npvec1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nepali_bert_npvec1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|83.5 MB| + +## References + +https://huggingface.co/nowalab/nepali-bert-npvec1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-newsbert_en.md b/docs/_posts/ahmedlone127/2023-09-09-newsbert_en.md new file mode 100644 index 00000000000000..e28d4d04e45574 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-newsbert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English newsbert BertEmbeddings from uclanlp +author: John Snow Labs +name: newsbert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`newsbert` is a English model originally trained by uclanlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/newsbert_en_5.1.1_3.0_1694259618522.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/newsbert_en_5.1.1_3.0_1694259618522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("newsbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("newsbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|newsbert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/uclanlp/newsbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-prompt_finetune_en.md b/docs/_posts/ahmedlone127/2023-09-09-prompt_finetune_en.md new file mode 100644 index 00000000000000..1ef62ad9cd0024 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-prompt_finetune_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English prompt_finetune BertEmbeddings from AndyJ +author: John Snow Labs +name: prompt_finetune +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`prompt_finetune` is a English model originally trained by AndyJ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/prompt_finetune_en_5.1.1_3.0_1694260942500.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/prompt_finetune_en_5.1.1_3.0_1694260942500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("prompt_finetune","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("prompt_finetune", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|prompt_finetune| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|408.0 MB| + +## References + +https://huggingface.co/AndyJ/prompt_finetune \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-pt_caselawbert_en.md b/docs/_posts/ahmedlone127/2023-09-09-pt_caselawbert_en.md new file mode 100644 index 00000000000000..72aedc0703d523 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-pt_caselawbert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English pt_caselawbert BertEmbeddings from SharedBailii +author: John Snow Labs +name: pt_caselawbert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pt_caselawbert` is a English model originally trained by SharedBailii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pt_caselawbert_en_5.1.1_3.0_1694266014749.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pt_caselawbert_en_5.1.1_3.0_1694266014749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("pt_caselawbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("pt_caselawbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pt_caselawbert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/SharedBailii/PT-CaseLawBert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-pt_legalbert_en.md b/docs/_posts/ahmedlone127/2023-09-09-pt_legalbert_en.md new file mode 100644 index 00000000000000..ad6c68aa3c6656 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-pt_legalbert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English pt_legalbert BertEmbeddings from SharedBailii +author: John Snow Labs +name: pt_legalbert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pt_legalbert` is a English model originally trained by SharedBailii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pt_legalbert_en_5.1.1_3.0_1694266151456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pt_legalbert_en_5.1.1_3.0_1694266151456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("pt_legalbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("pt_legalbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pt_legalbert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/SharedBailii/PT-LegalBert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-pt_pol_en.md b/docs/_posts/ahmedlone127/2023-09-09-pt_pol_en.md new file mode 100644 index 00000000000000..7168b1dde70c1c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-pt_pol_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English pt_pol BertEmbeddings from SharedBailii +author: John Snow Labs +name: pt_pol +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pt_pol` is a English model originally trained by SharedBailii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pt_pol_en_5.1.1_3.0_1694265453085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pt_pol_en_5.1.1_3.0_1694265453085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("pt_pol","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("pt_pol", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pt_pol| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/SharedBailii/PT-POL \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-romanian_bert_tweet_ro.md b/docs/_posts/ahmedlone127/2023-09-09-romanian_bert_tweet_ro.md new file mode 100644 index 00000000000000..3aaa3372223950 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-romanian_bert_tweet_ro.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Moldavian, Moldovan, Romanian romanian_bert_tweet BertEmbeddings from Iulian277 +author: John Snow Labs +name: romanian_bert_tweet +date: 2023-09-09 +tags: [bert, ro, open_source, fill_mask, onnx] +task: Embeddings +language: ro +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`romanian_bert_tweet` is a Moldavian, Moldovan, Romanian model originally trained by Iulian277. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/romanian_bert_tweet_ro_5.1.1_3.0_1694283360131.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/romanian_bert_tweet_ro_5.1.1_3.0_1694283360131.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("romanian_bert_tweet","ro") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("romanian_bert_tweet", "ro") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|romanian_bert_tweet| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|ro| +|Size:|466.5 MB| + +## References + +https://huggingface.co/Iulian277/ro-bert-tweet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-s3_v1_20_epochs_en.md b/docs/_posts/ahmedlone127/2023-09-09-s3_v1_20_epochs_en.md new file mode 100644 index 00000000000000..1bbcb5a006c2c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-s3_v1_20_epochs_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English s3_v1_20_epochs BertEmbeddings from AethiQs-Max +author: John Snow Labs +name: s3_v1_20_epochs +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s3_v1_20_epochs` is a English model originally trained by AethiQs-Max. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s3_v1_20_epochs_en_5.1.1_3.0_1694260577106.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s3_v1_20_epochs_en_5.1.1_3.0_1694260577106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("s3_v1_20_epochs","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("s3_v1_20_epochs", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|s3_v1_20_epochs| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/AethiQs-Max/s3-v1-20_epochs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-sae_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2023-09-09-sae_bert_base_uncased_en.md new file mode 100644 index 00000000000000..b9a4fb512b7dec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-sae_bert_base_uncased_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English sae_bert_base_uncased BertEmbeddings from jgammack +author: John Snow Labs +name: sae_bert_base_uncased +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sae_bert_base_uncased` is a English model originally trained by jgammack. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sae_bert_base_uncased_en_5.1.1_3.0_1694279737863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sae_bert_base_uncased_en_5.1.1_3.0_1694279737863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("sae_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("sae_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sae_bert_base_uncased| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/jgammack/SAE-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-scholarbert_100_wb_en.md b/docs/_posts/ahmedlone127/2023-09-09-scholarbert_100_wb_en.md new file mode 100644 index 00000000000000..f202cd31862621 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-scholarbert_100_wb_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English scholarbert_100_wb BertEmbeddings from globuslabs +author: John Snow Labs +name: scholarbert_100_wb +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scholarbert_100_wb` is a English model originally trained by globuslabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scholarbert_100_wb_en_5.1.1_3.0_1694279655954.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scholarbert_100_wb_en_5.1.1_3.0_1694279655954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("scholarbert_100_wb","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("scholarbert_100_wb", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scholarbert_100_wb| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/globuslabs/ScholarBERT_100_WB \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-scholarbert_10_en.md b/docs/_posts/ahmedlone127/2023-09-09-scholarbert_10_en.md new file mode 100644 index 00000000000000..28daa3d3d42423 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-scholarbert_10_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English scholarbert_10 BertEmbeddings from globuslabs +author: John Snow Labs +name: scholarbert_10 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scholarbert_10` is a English model originally trained by globuslabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scholarbert_10_en_5.1.1_3.0_1694279085983.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scholarbert_10_en_5.1.1_3.0_1694279085983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("scholarbert_10","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("scholarbert_10", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scholarbert_10| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/globuslabs/ScholarBERT_10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-scholarbert_10_wb_en.md b/docs/_posts/ahmedlone127/2023-09-09-scholarbert_10_wb_en.md new file mode 100644 index 00000000000000..a3511f63b3c5e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-scholarbert_10_wb_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English scholarbert_10_wb BertEmbeddings from globuslabs +author: John Snow Labs +name: scholarbert_10_wb +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scholarbert_10_wb` is a English model originally trained by globuslabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scholarbert_10_wb_en_5.1.1_3.0_1694279935293.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scholarbert_10_wb_en_5.1.1_3.0_1694279935293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("scholarbert_10_wb","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("scholarbert_10_wb", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scholarbert_10_wb| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/globuslabs/ScholarBERT_10_WB \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-scholarbert_1_en.md b/docs/_posts/ahmedlone127/2023-09-09-scholarbert_1_en.md new file mode 100644 index 00000000000000..41090287433361 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-scholarbert_1_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English scholarbert_1 BertEmbeddings from globuslabs +author: John Snow Labs +name: scholarbert_1 +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scholarbert_1` is a English model originally trained by globuslabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scholarbert_1_en_5.1.1_3.0_1694279368543.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scholarbert_1_en_5.1.1_3.0_1694279368543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("scholarbert_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("scholarbert_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scholarbert_1| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/globuslabs/ScholarBERT_1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-scholarbert_en.md b/docs/_posts/ahmedlone127/2023-09-09-scholarbert_en.md new file mode 100644 index 00000000000000..4c0b4f162fd3e7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-scholarbert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English scholarbert BertEmbeddings from globuslabs +author: John Snow Labs +name: scholarbert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scholarbert` is a English model originally trained by globuslabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scholarbert_en_5.1.1_3.0_1694278560520.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scholarbert_en_5.1.1_3.0_1694278560520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("scholarbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("scholarbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scholarbert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/globuslabs/ScholarBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-spacebert_en.md b/docs/_posts/ahmedlone127/2023-09-09-spacebert_en.md new file mode 100644 index 00000000000000..06af2bc491452a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-spacebert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English spacebert BertEmbeddings from icelab +author: John Snow Labs +name: spacebert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spacebert` is a English model originally trained by icelab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spacebert_en_5.1.1_3.0_1694266124128.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spacebert_en_5.1.1_3.0_1694266124128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("spacebert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("spacebert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spacebert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/icelab/spacebert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-spacescibert_en.md b/docs/_posts/ahmedlone127/2023-09-09-spacescibert_en.md new file mode 100644 index 00000000000000..97aa84a1c3942f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-spacescibert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English spacescibert BertEmbeddings from icelab +author: John Snow Labs +name: spacescibert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spacescibert` is a English model originally trained by icelab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spacescibert_en_5.1.1_3.0_1694266250257.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spacescibert_en_5.1.1_3.0_1694266250257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("spacescibert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("spacescibert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spacescibert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|409.9 MB| + +## References + +https://huggingface.co/icelab/spacescibert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-tendencias_en.md b/docs/_posts/ahmedlone127/2023-09-09-tendencias_en.md new file mode 100644 index 00000000000000..74de16a8e716da --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-tendencias_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tendencias BertEmbeddings from edwatanabe +author: John Snow Labs +name: tendencias +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tendencias` is a English model originally trained by edwatanabe. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tendencias_en_5.1.1_3.0_1694283750490.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tendencias_en_5.1.1_3.0_1694283750490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("tendencias","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("tendencias", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tendencias| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/edwatanabe/tendencias \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-test_ru.md b/docs/_posts/ahmedlone127/2023-09-09-test_ru.md new file mode 100644 index 00000000000000..f38da753fdb9a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-test_ru.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Russian test BertEmbeddings from k0t1k +author: John Snow Labs +name: test +date: 2023-09-09 +tags: [bert, ru, open_source, fill_mask, onnx] +task: Embeddings +language: ru +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test` is a Russian model originally trained by k0t1k. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ru_5.1.1_3.0_1694284796336.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ru_5.1.1_3.0_1694284796336.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("test","ru") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("test", "ru") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|ru| +|Size:|43.8 MB| + +## References + +https://huggingface.co/k0t1k/test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_cola_en.md b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_cola_en.md new file mode 100644 index 00000000000000..47a9f61e5832be --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_cola_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_mlm_glue_cola BertEmbeddings from muhtasham +author: John Snow Labs +name: tiny_mlm_glue_cola +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_mlm_glue_cola` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_mlm_glue_cola_en_5.1.1_3.0_1694284657538.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_mlm_glue_cola_en_5.1.1_3.0_1694284657538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("tiny_mlm_glue_cola","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("tiny_mlm_glue_cola", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_mlm_glue_cola| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-glue-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_mnli_en.md b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_mnli_en.md new file mode 100644 index 00000000000000..72cc2d69973004 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_mnli_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_mlm_glue_mnli BertEmbeddings from muhtasham +author: John Snow Labs +name: tiny_mlm_glue_mnli +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_mlm_glue_mnli` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_mlm_glue_mnli_en_5.1.1_3.0_1694284719722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_mlm_glue_mnli_en_5.1.1_3.0_1694284719722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("tiny_mlm_glue_mnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("tiny_mlm_glue_mnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_mlm_glue_mnli| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-glue-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_mrpc_en.md b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_mrpc_en.md new file mode 100644 index 00000000000000..55ed9c9eb86c27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_mrpc_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_mlm_glue_mrpc BertEmbeddings from muhtasham +author: John Snow Labs +name: tiny_mlm_glue_mrpc +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_mlm_glue_mrpc` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_mlm_glue_mrpc_en_5.1.1_3.0_1694284793871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_mlm_glue_mrpc_en_5.1.1_3.0_1694284793871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("tiny_mlm_glue_mrpc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("tiny_mlm_glue_mrpc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_mlm_glue_mrpc| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-glue-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_qnli_en.md b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_qnli_en.md new file mode 100644 index 00000000000000..23047374c2645a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_qnli_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_mlm_glue_qnli BertEmbeddings from muhtasham +author: John Snow Labs +name: tiny_mlm_glue_qnli +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_mlm_glue_qnli` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_mlm_glue_qnli_en_5.1.1_3.0_1694284869990.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_mlm_glue_qnli_en_5.1.1_3.0_1694284869990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("tiny_mlm_glue_qnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("tiny_mlm_glue_qnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_mlm_glue_qnli| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-glue-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_qqp_en.md b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_qqp_en.md new file mode 100644 index 00000000000000..be40c3d4003454 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_glue_qqp_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_mlm_glue_qqp BertEmbeddings from muhtasham +author: John Snow Labs +name: tiny_mlm_glue_qqp +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_mlm_glue_qqp` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_mlm_glue_qqp_en_5.1.1_3.0_1694284948621.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_mlm_glue_qqp_en_5.1.1_3.0_1694284948621.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("tiny_mlm_glue_qqp","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("tiny_mlm_glue_qqp", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_mlm_glue_qqp| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-glue-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_snli_en.md b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_snli_en.md new file mode 100644 index 00000000000000..ca327f395c682b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-tiny_mlm_snli_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tiny_mlm_snli BertEmbeddings from muhtasham +author: John Snow Labs +name: tiny_mlm_snli +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_mlm_snli` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_mlm_snli_en_5.1.1_3.0_1694283488441.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_mlm_snli_en_5.1.1_3.0_1694283488441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("tiny_mlm_snli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("tiny_mlm_snli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_mlm_snli| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-snli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-tod_bert_jnt_en.md b/docs/_posts/ahmedlone127/2023-09-09-tod_bert_jnt_en.md new file mode 100644 index 00000000000000..ce799c56d6f12b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-tod_bert_jnt_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English tod_bert_jnt BertEmbeddings from jasonwu +author: John Snow Labs +name: tod_bert_jnt +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tod_bert_jnt` is a English model originally trained by jasonwu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tod_bert_jnt_en_5.1.1_3.0_1694278507559.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tod_bert_jnt_en_5.1.1_3.0_1694278507559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("tod_bert_jnt","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("tod_bert_jnt", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tod_bert_jnt| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/jasonwu/ToD-BERT-jnt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-turkish_mbertmodel_mberttok_en.md b/docs/_posts/ahmedlone127/2023-09-09-turkish_mbertmodel_mberttok_en.md new file mode 100644 index 00000000000000..56d140915691c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-turkish_mbertmodel_mberttok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English turkish_mbertmodel_mberttok BertEmbeddings from hgiyt +author: John Snow Labs +name: turkish_mbertmodel_mberttok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_mbertmodel_mberttok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_mbertmodel_mberttok_en_5.1.1_3.0_1694265250672.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_mbertmodel_mberttok_en_5.1.1_3.0_1694265250672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("turkish_mbertmodel_mberttok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("turkish_mbertmodel_mberttok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkish_mbertmodel_mberttok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|525.2 MB| + +## References + +https://huggingface.co/hgiyt/tr-mbertmodel-mberttok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-turkish_mbertmodel_monotok_adapter_en.md b/docs/_posts/ahmedlone127/2023-09-09-turkish_mbertmodel_monotok_adapter_en.md new file mode 100644 index 00000000000000..fde120f67aa5b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-turkish_mbertmodel_monotok_adapter_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English turkish_mbertmodel_monotok_adapter BertEmbeddings from hgiyt +author: John Snow Labs +name: turkish_mbertmodel_monotok_adapter +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_mbertmodel_monotok_adapter` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_mbertmodel_monotok_adapter_en_5.1.1_3.0_1694265394331.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_mbertmodel_monotok_adapter_en_5.1.1_3.0_1694265394331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("turkish_mbertmodel_monotok_adapter","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("turkish_mbertmodel_monotok_adapter", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkish_mbertmodel_monotok_adapter| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|412.6 MB| + +## References + +https://huggingface.co/hgiyt/tr-mbertmodel-monotok-adapter \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-turkish_mbertmodel_monotok_en.md b/docs/_posts/ahmedlone127/2023-09-09-turkish_mbertmodel_monotok_en.md new file mode 100644 index 00000000000000..44c25a569f9151 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-turkish_mbertmodel_monotok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English turkish_mbertmodel_monotok BertEmbeddings from hgiyt +author: John Snow Labs +name: turkish_mbertmodel_monotok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_mbertmodel_monotok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_mbertmodel_monotok_en_5.1.1_3.0_1694265535952.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_mbertmodel_monotok_en_5.1.1_3.0_1694265535952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("turkish_mbertmodel_monotok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("turkish_mbertmodel_monotok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkish_mbertmodel_monotok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|412.6 MB| + +## References + +https://huggingface.co/hgiyt/tr-mbertmodel-monotok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-turkish_monomodel_mberttok_en.md b/docs/_posts/ahmedlone127/2023-09-09-turkish_monomodel_mberttok_en.md new file mode 100644 index 00000000000000..b9a1599559d93c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-turkish_monomodel_mberttok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English turkish_monomodel_mberttok BertEmbeddings from hgiyt +author: John Snow Labs +name: turkish_monomodel_mberttok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_monomodel_mberttok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_monomodel_mberttok_en_5.1.1_3.0_1694265682717.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_monomodel_mberttok_en_5.1.1_3.0_1694265682717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("turkish_monomodel_mberttok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("turkish_monomodel_mberttok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkish_monomodel_mberttok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|524.2 MB| + +## References + +https://huggingface.co/hgiyt/tr-monomodel-mberttok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-turkish_monomodel_monotok_en.md b/docs/_posts/ahmedlone127/2023-09-09-turkish_monomodel_monotok_en.md new file mode 100644 index 00000000000000..663567c4c5c30a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-turkish_monomodel_monotok_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English turkish_monomodel_monotok BertEmbeddings from hgiyt +author: John Snow Labs +name: turkish_monomodel_monotok +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_monomodel_monotok` is a English model originally trained by hgiyt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_monomodel_monotok_en_5.1.1_3.0_1694265818291.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_monomodel_monotok_en_5.1.1_3.0_1694265818291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("turkish_monomodel_monotok","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("turkish_monomodel_monotok", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkish_monomodel_monotok| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/hgiyt/tr-monomodel-monotok \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-vbert_2021_large_en.md b/docs/_posts/ahmedlone127/2023-09-09-vbert_2021_large_en.md new file mode 100644 index 00000000000000..64fbe01a0a7703 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-vbert_2021_large_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English vbert_2021_large BertEmbeddings from VMware +author: John Snow Labs +name: vbert_2021_large +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vbert_2021_large` is a English model originally trained by VMware. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vbert_2021_large_en_5.1.1_3.0_1694258767377.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vbert_2021_large_en_5.1.1_3.0_1694258767377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("vbert_2021_large","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("vbert_2021_large", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vbert_2021_large| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/VMware/vbert-2021-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-wordpred_arabert_en.md b/docs/_posts/ahmedlone127/2023-09-09-wordpred_arabert_en.md new file mode 100644 index 00000000000000..3de4403923a8f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-wordpred_arabert_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English wordpred_arabert BertEmbeddings from rowidabelaal +author: John Snow Labs +name: wordpred_arabert +date: 2023-09-09 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wordpred_arabert` is a English model originally trained by rowidabelaal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wordpred_arabert_en_5.1.1_3.0_1694260416937.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wordpred_arabert_en_5.1.1_3.0_1694260416937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("wordpred_arabert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("wordpred_arabert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wordpred_arabert| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/rowidabelaal/wordpred_arabert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-09-09-xtreme_squad_bert_base_multilingual_cased_xx.md b/docs/_posts/ahmedlone127/2023-09-09-xtreme_squad_bert_base_multilingual_cased_xx.md new file mode 100644 index 00000000000000..25d1e020185df7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-09-xtreme_squad_bert_base_multilingual_cased_xx.md @@ -0,0 +1,93 @@ +--- +layout: model +title: Multilingual xtreme_squad_bert_base_multilingual_cased BertEmbeddings from dyyyyyyyy +author: John Snow Labs +name: xtreme_squad_bert_base_multilingual_cased +date: 2023-09-09 +tags: [bert, xx, open_source, fill_mask, onnx] +task: Embeddings +language: xx +edition: Spark NLP 5.1.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xtreme_squad_bert_base_multilingual_cased` is a Multilingual model originally trained by dyyyyyyyy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xtreme_squad_bert_base_multilingual_cased_xx_5.1.1_3.0_1694266754297.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xtreme_squad_bert_base_multilingual_cased_xx_5.1.1_3.0_1694266754297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =BertEmbeddings.pretrained("xtreme_squad_bert_base_multilingual_cased","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = BertEmbeddings + .pretrained("xtreme_squad_bert_base_multilingual_cased", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xtreme_squad_bert_base_multilingual_cased| +|Compatibility:|Spark NLP 5.1.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|665.0 MB| + +## References + +https://huggingface.co/dyyyyyyyy/XTREME_squad_BERT-base-multilingual-cased \ No newline at end of file